Sim vs OpenClaw
Sim is the open-source AI workspace where teams build, deploy, and manage AI agents visually, conversationally, or with code. Here is how Sim compares to OpenClaw on platform architecture, AI capabilities, integrations, pricing, security, and support. Every fact below is sourced and dated.
Sim is an open-source AI workspace for building, deploying, and managing AI agents. This page compares Sim to OpenClaw across platform architecture, AI capabilities, integrations, pricing, security and compliance, observability, and support, using sourced, dated facts for buyers evaluating both platforms.
What is Sim?
Sim is the open-source AI workspace where teams build, deploy, and manage AI agents, connecting 1,000+ integrations and every major LLM to automate real work visually, conversationally, or with code.
What is OpenClaw?
OpenClaw is a free, open-source, self-hosted personal AI agent that runs on a user's own machine or server and connects to messaging platforms (WhatsApp, Telegram, Slack, Discord, Signal, iMessage, Microsoft Teams, and others) as its primary interface, extensible via a Skills plugin system and the ClawHub marketplace. It is not a visual workflow/automation builder like Sim, n8n, or Power Automate.
Sim vs OpenClaw: feature-by-feature comparison
CompareSim vs OpenClaw
Sim
OpenClaw
Platform
Builder type
Visual canvas, chat, or codeVisual drag-and-drop canvas, natural-language (Chat), or code (API/SDK)
Conversational config-driven agent, not a visual builderConversational, config-driven personal AI agent gateway, not a visual or drag-and-drop workflow/agent builder. Behavior is set via a JSON configuration file (openclaw.json) and Markdown Skill files, and the agent is operated by sending it chat messages, not by wiring blocks on a canvas.. The docs describe OpenClaw as "a self-hosted gateway that connects your favorite chat apps...to AI coding agents," configured through a CLI (openclaw onboard, openclaw channels login) and JSON/Markdown files, not a graphical builder.
Learning curve
Low, plus natural-language Chat for non-technical usersLow for visual building; natural-language Chat surface for non-technical builders. Chat lets users describe a workflow in plain language and have Sim build it.
Technical setup, but simple chat once configuredModerate to steep for initial self-hosted setup, low for day-to-day chat use once running. Installing OpenClaw requires Node.js 22.19+/24, a package manager (pnpm/npm/bun), CLI onboarding commands, and editing JSON configuration for channels, providers, and security policy (e.g. DM pairing, sandbox mode). Once running, interacting with the agent is plain natural-language chat.
Self-hosting
Yes: self-hosting is the only deployment model. OpenClaw runs as a single Gateway process on the user's own machine or server. There is no OpenClaw-operated hosted/SaaS version.. Docs describe the Gateway as running locally and being "the single source of truth for sessions, routing, and channel connections," with a local workspace at ~/.openclaw/workspace.
Deployment options
Cloud-hosted or self-hosted, no mid-tier VPC optionCloud-hosted (managed, multi-tenant SaaS) or self-hosted (Docker/Kubernetes). No documented managed single-tenant/VPC hosting tier in between. The Enterprise plan's only hosting-related row in the pricing comparison table is a boolean "Self Hosting" flag; there is no dedicated-instance/VPC offering.
Local install, Docker, or from source; no hosted optionLocal install via npm/pnpm/bun on macOS, Windows, or Linux; from-source build via a pnpm workspace; Docker/docker-compose; plus companion macOS app and iOS/Android mobile "nodes" that connect to a locally run Gateway. The GitHub repo documents `npm install -g openclaw@latest` plus `openclaw onboard --install-daemon` as the recommended path, alongside from-source and Docker installs, and platform-specific companion apps (Windows Hub, macOS app, iOS/Android nodes).
Templates
No workflow templates in the visual-builder sense; OpenClaw has no workflow canvas. ClawHub instead offers 60,000+ community-built Skills as installable starter packages for specific tasks.. ClawHub's live registry lists over 60,000 community-built skills and 56,000+ certified skills, the closest analog to a template gallery, but each is a Markdown instruction package installed into the agent, not a prebuilt multi-step workflow.
License
Apache 2.0Apache License 2.0
MIT license, non-profit Foundation governanceMIT License (permissive open source), stewarded by the independent, non-profit OpenClaw Foundation, not a single vendor company. The GitHub repository's LICENSE file confirms MIT licensing. Governance passed from creator Peter Steinberger to a community-elected Foundation board after he joined OpenAI in February 2026. OpenAI is a Foundation sponsor (inference support and Codex Security scanning) but does not own the project.
Environment promotion
Yes: fork a whole workspace into a dev/qa/prod-style child, diff it, and promote or roll back changes in either direction. Credential and env-var remapping is required before every promote, so secrets are never silently copied across environments. Gated to Enterprise plan on hosted Sim, or a FORKING_ENABLED flag on self-hosted deployments.
No dev/staging/prod conceptN/A: no dev/staging/production environment-promotion concept exists. OpenClaw is a single running agent instance configured by one JSON file, not a deployable multi-stage application.. There is no feature for forking or promoting a full agent configuration/project between separate environments; configuration changes apply directly to the running Gateway.
Version control
Deployment rollback plus Copilot edit diff/revertDeployed-version history with rollback for every workflow; server-persisted checkpoint/revert and visual diff (accept/reject) specifically for Copilot AI edits. Manual drag-and-drop undo/redo is client-side/localStorage only (capped at 100 ops, 5 stacks), not server-synced across devices. Deployment history does not include an arbitrary version-to-version diff tool, and knowledge base documents have no version history.
No native version history, diff/compare, or rollback feature for agent configuration or Skills; users can optionally track their own config/skill files in an external Git repository. Skills and memory are plain files on disk (SKILL.md, MEMORY.md, openclaw.json), which a user can manually place under their own Git repository for versioning. OpenClaw itself ships no built-in change-history or restore UI for these files.
Realtime collaboration
No: OpenClaw's security model assumes a single trusted operator per Gateway instance, not multiple simultaneous users collaboratively editing the same agent configuration or session with live cursors/synced state.. The security documentation states the design is a "single-user, personal-assistant model," which excludes any live multi-user co-editing concept.
Native file storage
Yes: a native Files area with folder hierarchy, link-based sharing (public, password, email OTP, or SSO auth), and a workspace-level Recently Deleted view covering workflows, tables, knowledge bases, files, and folders. Admins can restrict which share-auth modes (public/password/email/SSO) a permission group is allowed to use.
No: OpenClaw has no cloud file-storage product of its own (no folder hierarchy, link-based sharing with password/SSO, or deleted-item recovery). It reads/writes files directly on the operator's own local filesystem or connected apps (e.g. via MCP servers, channel attachments) inside a sandboxed workspace directory.. Tool access defaults to sandbox-isolated directories under the local workspace (~/.openclaw/workspace). There is no first-party hosted file-storage/sharing surface distinct from the local filesystem.
Sub-workflows (composition)
No: OpenClaw's optional Lobster workflow shell has no step type for invoking another saved workflow file as a nested sub-step. Sub-agents (sessions_spawn) delegate a task to a whole separate agent session, not a call-and-wait step inside a defined multi-step pipeline.. Lobster's step types are run/command (shell/CLI), pipeline (native stages like llm.invoke), and approval (gates); none reference invoking a second .lobster/YAML/JSON workflow file as a step. Sub-agents are the closest related feature but compose whole agent sessions, not saved workflow definitions, and even that requires an explicit sessions_yield to block for a result rather than a built-in composition primitive.
Pricing
Pricing model
Credit-based billing, BYOK exempt from capsCredit-based usage billing (Stripe), with bring-your-own-key exemption from metered caps
Free software, pay only your own model providerFree and open source (MIT license); no OpenClaw subscription fee. Users separately pay their chosen LLM provider (Anthropic, OpenAI, Google, etc.) for model usage, or run a local model at no marginal API cost.. There is no OpenClaw-branded paid plan: the software itself carries no license fee and there is no hosted SaaS tier. The only recurring cost is whichever model provider/API the operator configures.
Entry paid plan
Pro plan at $25/user/monthPro: $25 per user/month
N/A, no paid plan existsN/A: there is no paid OpenClaw plan or tier. The software is free under the MIT license.. No pricing page or paid-tier documentation exists for OpenClaw itself. Costs incurred are entirely third-party (LLM provider API usage, optional TTS/media-generation provider fees, hosting for a VPS if not run on a personal machine).
Free tier
Yes: the entire product is free and open source under the MIT license; there is no metered or gated free tier because there is no paid tier at all.. Unlike a typical vendor "free tier" that caps usage, OpenClaw imposes no OpenClaw-side usage limits. Only the configured LLM provider's own rate limits/costs apply.
Bring your own key
Yes, and mandatory: OpenClaw requires the operator to supply their own API credentials/OAuth login for whichever model provider(s) they configure (Anthropic, OpenAI, Google, or any OpenAI-compatible endpoint); there is no OpenClaw-hosted model access.. Onboarding documentation walks through provider-specific auth flows (e.g. `openclaw models auth paste-token --provider anthropic`, `openclaw models auth login --provider openai-codex`). BYOK is the only supported model-access model.
Security & compliance
SOC 2
No: OpenClaw is a self-hosted open-source project run by a non-profit Foundation, not a vendor selling a hosted service, and publishes no SOC 2 report.. No SOC 2 attestation, trust center, or audit report exists for OpenClaw. Responsibility for infrastructure security rests entirely with whoever self-hosts the Gateway.
Data residency
Full control via self-hosting; Cloud region toggle is global, not per-customerFull data control via self-hosting (Docker/Kubernetes); data never leaves customer infrastructure when self-hosted. On Sim Cloud, async job execution has an internal US/EU region toggle, but it is deployment-wide, not a customer-selectable per-workspace residency option
Yes, by construction: because OpenClaw is self-hosted only, all agent data (sessions, memory files, credentials) resides wherever the operator chooses to run the Gateway (laptop, homelab, or their own VPS/cloud region), giving complete control over data location with no vendor-side residency question.. The OpenClaw Ecosystem page states data lives "where you choose, laptop, homelab, or VPS," a direct consequence of there being no vendor-operated cloud service.
Role-based access control
No: OpenClaw has no role-based access control system. Its security model is a "single-user, personal-assistant model" with one trusted operator per Gateway, not multiple roles/permission tiers for different users of the same instance.. Access control that does exist is channel/message-level (DM pairing policy, group allowlists, per-agent tool allow/deny), not a user-role permission matrix.
Audit logging
Local audit CLI + redacted JSONL transcripts, not a central log productPartial: a local `openclaw security audit` CLI command checks inbound access policy, tool blast radius, filesystem permissions, and network exposure, and session transcripts are stored as local JSONL files with sensitive content redacted by default. This is a local diagnostic/log-file feature, not a centralized, exportable audit-log product.. Findings are grouped by severity with checkId keys (e.g. gateway.bind_no_auth). Transcripts live at ~/.openclaw/agents/<agentId>/sessions/*.jsonl, accessible to any process with filesystem access to that path, so there is no access-controlled central audit store.
Additional compliance
SOC2SOC2. Self-hosting is the primary lever Sim offers for data-residency-sensitive compliance needs beyond SOC2, rather than additional certifications.
No compliance certifications (no HIPAA, ISO 27001, GDPR-specific attestation, PCI, or FedRAMP). As open-source, self-hosted software from a non-profit Foundation, OpenClaw is not the kind of vendor entity that typically pursues these certifications; compliance posture depends entirely on how and where the operator self-hosts it.. China restricted state enterprises and government agencies from deploying OpenClaw in March 2026 over security concerns, per Wikipedia's history summary, a data point on the compliance/trust landscape rather than a certification.
Model & tool governance
Yes: enterprise "permission groups" let an admin allow-list/deny-list specific LLM providers and models, and separately deny specific tools/integrations (or disable all MCP or custom tools) per group, layered on top of workspace admin/write/read roles. This does not control whether an LLM provider retains prompts. Sim offers no "zero data retention" mode or governed AI gateway. A separate, Enterprise-gated feature lets orgs set a log-retention window and redact PII, but that only controls how long Sim itself keeps execution logs.
Yes, at the single-operator level: OpenClaw supports per-agent tool allow/deny lists, sandbox-level tool filters, and per-model-provider configuration, so an operator can restrict which tools/models a given agent may use. This is configured by one trusted operator, not enforced org-wide across multiple admin-managed users.. Documented as a three-gate system (agent-level tools.allow/deny, sandbox-level tools.allow, and container network access), plus explicit provider/model selection per agent in configuration.
Credential governance
Yes: shared credentials (connected accounts, service accounts, workspace secrets) are their own nested permission level (Member/Admin) below organization and workspace roles, and enterprise permission groups can further allow-list specific integrations and restrict which file-share auth modes (public/password/email/SSO) a group may use. A user's personal environment variables/secrets are never shared or inherited by anyone, including org owners/admins.
No: OpenClaw has no per-role credential-scoping system, since there are no multiple roles to scope. Its security docs flag that home-directory credential paths (~/.aws, ~/.ssh, ~/.npm, etc.) must be explicitly blocked from sandbox mounts as a hardening step, rather than being governed by a built-in fine-grained credential-access policy layer.. The docs list credential-root directories the sandbox blocks by default (docker.sock, /etc, /proc, /sys, /dev, plus ~/.aws, ~/.cargo, ~/.config, ~/.docker, ~/.gnupg, ~/.netrc, ~/.npm, ~/.ssh), a deny-list hardening measure, not a positive credential-governance feature.
Single sign-on (SSO)
No: OpenClaw has no SAML/OIDC single sign-on feature. Its access model authenticates individual senders on connected messaging channels (DM pairing, allowlists), a single-operator personal tool, not an organization with a directory of employees signing in via an identity provider.. SSO and organization provisioning are out of scope for the "single-user, personal-assistant model" OpenClaw's security documentation describes.
Vetted first-party integrations
Yes: every one of Sim's 302 blocks is first-party authored and code-reviewed through the standard pull-request process in the main Sim repository; there is no public marketplace where an arbitrary third party can publish and have other users install executable tool code without going through Sim's own review. Custom code steps run inside Sim's own isolated-vm sandbox rather than as an installable third-party skill package, so the supply-chain trust boundary is Sim's codebase review, not an open registry.
No: Skills mainly come from ClawHub, an open marketplace where any third-party developer can publish and any user can install executable Markdown/code Skill packages, not a first-party catalog authored by OpenClaw. Researchers documented 283 ClawHub skills (about 7.1% of the registry) leaking API keys and other credentials, and a separate scan found 24 accounts distributing over 600 malicious skills before scanning existed.. OpenClaw has since added a ClawScan pipeline (static analysis, VirusTotal, and NVIDIA SkillSpector as of June 2026) that assigns each published skill a Clean/Suspicious/Malicious verdict and a Skill Card, but its docs still tell users to treat third-party skills as untrusted code, and the marketplace remains open to any publisher rather than vendor-authored.
PII redaction
Partial: log redaction only, not conversation-content PII detectionPartial: session logging redacts sensitive tool summaries and URLs by default (logging.redactSensitive: "tools"), but this is generic sensitive-data log redaction, not a dedicated, named PII-detection feature (e.g. SSNs, credit card numbers) applied to conversation content itself.. Redaction applies to logging output only, not to what the agent itself sees or processes mid-conversation.
Custom data retention
Yes, operator-configurable: isolated sub-agent/cron sessions are pruned after a retention window (24 hours by default), and because all data lives in local files (session JSONL transcripts, memory Markdown files), the self-hosting operator has full control over retention (including deleting files immediately).. The default 24-hour retention applies specifically to isolated cron-job sessions; the main session's own history and memory files persist until the operator manually prunes them, giving complete operator-side control rather than a vendor-set policy.
White-labeling
No: OpenClaw has no white-labeling feature. As a personal, self-hosted agent, not a product a business deploys to its own end customers under its own brand, rebranding the product UI/name is not a use case the docs address.. No documentation describes replacing OpenClaw branding for a deployed customer-facing product; the concept does not map cleanly onto a personal-assistant tool the way it does for a workflow platform with deployed apps.
AI capabilities
Multi-LLM support
21 providers incl. OpenAI, Anthropic, Google, Bedrock21 provider integrations (OpenAI, Anthropic, Google/Gemini, Azure OpenAI, Azure Anthropic, Groq, Cerebras, Mistral, xAI, Bedrock, Vertex, Ollama, OpenRouter, and more). apps/sim/providers/models.ts defines 21 provider entries; openrouter/litellm/vllm/ollama resolve models dynamically at runtime rather than from a hardcoded model list.
Yes: bundled support for Anthropic Claude, OpenAI (via Codex OAuth), and Google Gemini, plus any OpenAI-compatible endpoint including local runtimes like Ollama. OpenClaw ships with the pi-ai model catalog for Anthropic, OpenAI, and Google Gemini (auth via CLI login/token flows), and supports local models (Ollama, auto-detected at http://127.0.0.1:11434/v1) and other OpenAI-compatible providers (Moonshot/Kimi, Cerebras, MiniMax, DeepSeek, Groq, xAI, and others).
Agent reasoning blocks
No block-based builder; reasoning is the whole agent loopN/A in the block-based sense: OpenClaw has no visual builder with distinct "reasoning" vs. "routing" node types. The entire agent is a single conversational reasoning loop, with optional sub-agent delegation, not composed from discrete blocks.. Reasoning happens inside the model's own agent loop per turn. The closest structural analog is spawning a sub-agent for a distinct sub-task, not a dedicated "agent block" placed on a canvas.
Natural-language building
Yes, in that natural language is the entire interaction model, but this is not "building a workflow" from a prompt: there is no workflow artifact for a prompt to generate. Configuration (channels, providers, security policy) is done via JSON files and CLI commands, not natural-language authoring.. OpenClaw's design splits operational config (JSON/CLI, technical) from agent interaction (chat, natural language); the two are not the same axis as a workflow-builder's "describe it and get an editable workflow" feature.
Knowledge base / RAG
Semantic search over own Markdown notes, not a general KB/RAG modulePartial: a built-in semantic-search memory system (memorySearch) indexes the operator's own Markdown notes for natural-language retrieval, but there is no dedicated knowledge-base module for ingesting arbitrary documents (PDF, DOCX, websites) into a managed vector database the way a workflow platform's KB module does.. memorySearch uses vector embeddings over the user's own Markdown files (daily notes, MEMORY.md) for semantic recall. Broader document ingestion/RAG over arbitrary file types relies on external MCP servers or Skills, not a first-party KB feature.
MCP support
Yes: native MCP client support over both stdio and HTTP/SSE transports, connecting to any published MCP server by adding an mcpServers block to the OpenClaw config. Compatible with "the entire published ecosystem of MCP servers" (e.g. GitHub, Notion, Postgres, Slack). Whether OpenClaw itself can be published as an MCP server for external tools to call is undocumented (see mcpPublishing).
Evaluation & guardrails
LLM-judge Evaluator plus Guardrails validation blockEvaluator block (LLM-judge scoring against user-defined named metrics) and Guardrails block (JSON validity, regex, RAG/hallucination scoring, PII detection/masking). These are per-call scoring/validation primitives, not a batch golden-dataset eval-suite runner or A/B prompt-testing harness.
No dedicated eval/regression-testing framework for agent behavior; safety controls instead take the form of exec approval gates, sandboxing, and skill security scanning (ClawScan/SkillSpector/VirusTotal), not a test-dataset evaluation feature.. The security documentation covers exec approvals, sandbox tiers, and DM/group access policy, not an evaluation harness for scoring agent output quality against expected results.
Human-in-the-loop
Yes: a per-command exec-approval system prompts the operator with Allow Once / Always Allow / Don't Allow for new command patterns before the agent can run them, distinct from a plain delay step. One of three permission gates (agent-level tool allow/deny, sandbox-level tool filter, and exec approvals), configurable per-agent via a security/ask mode. This is host command execution approval specifically, not a general-purpose "pause and wait for any human input" workflow node.
Generative media
Yes: documented tools for image generation, video generation (text-to-video, image-to-video, video-to-video), music/audio generation, and text-to-speech, each running asynchronously except TTS which runs synchronously. The image_generate, video_generate, and music_generate tools post results into the chat session when ready. TTS defaults to ElevenLabs but also supports Azure Speech and Google Cloud TTS, with SSML/voice customization.
Dynamic tool use
No: an Agent block calls tools the workflow author explicitly added to it at build time, rather than browsing and picking from a broader pool (e.g. an entire MCP server catalog) at inference time. Runtime MCP "discovery" exists to resolve/refresh the schema of an already-configured tool. The model does not browse or choose from the server's full tool list.
Yes: the agent dynamically selects among its configured tools, connectors, and installed Skills at runtime based on the request, rather than following a pre-wired sequence of steps chosen at build time. This is the core operating model described throughout the docs (tool/skill dispatch decided per-turn by the agent), a consequence of there being no visual builder with pre-wired steps.
Automatic model fallback
No: a failed or rate-limited LLM call is retried using Sim's own hosted API keys for the same model, rather than automatically switching to a different model or provider. A "fallback" comment in the provider layer refers to rotating among Sim's own hosted API keys for the same model, not switching models.
Not publicly documentedUnknown. OpenClaw documentation does not describe an automatic fallback to a different model or provider when the configured model errors or is rate-limited.
Agent skills
Yes: named, reusable "Agent Skills" (built on the open Agent Skills / SKILL.md format) that agents load on demand via progressive disclosure, editable in-app or imported from a SKILL.md file or GitHub URL. Only the skill name and description sit in the agent's system prompt (~50-100 tokens each); the full instructions load into context only when the agent calls load_skill.
Yes: Skills are named, reusable Markdown instruction packages (SKILL.md plus optional reference files/scripts) that a builder writes once, and the agent invokes by name or automatically when context matches, installable individually from ClawHub, git, or a local path. Skills follow the AgentSkills specification, support YAML frontmatter for gating (OS, environment variables, config flags) and slash-command exposure, and are resolved via a documented precedence order across workspace, project, personal, and managed/bundled skill directories.
Native chat deployment
N/A: chat is the native interface, not a separate deploy targetN/A: OpenClaw's entire product is a chat surface (messaging-platform channels), so there is no separate "deploy as a public chat widget" feature the way a workflow builder has. Chat is the interface itself, not an optional deployment target.. The agent is reached through the messaging channels the operator has connected it to (WhatsApp, Telegram, Slack, etc.) or a local Web Control UI. There is no feature to publish a standalone, unauthenticated public-facing chat widget for arbitrary website visitors.
Parallel execution
Yes: a native Parallel block fans a run out into concurrent branches (fixed count or one per list item) and joins their results back into the workflow automatically. Contained blocks run concurrently instead of sequentially, either a fixed number of times or once per item in a list/collection, and each branch's output aggregates for downstream blocks.
Yes: sub-agents can run in parallel, working simultaneously on separate tasks (e.g. research, content generation, verification) and report back to the requesting session, up to a documented 2-level nesting depth (main session can spawn depth-1 sub-agents, which can spawn depth-2 workers, where depth-2 spawning further sub-agents is denied). Each sub-agent gets its own session identifier, context window, and execution environment (with optional sandboxing), isolated from the main session and from sibling sub-agents.
Agent2Agent (A2A) protocol
No native support: OpenClaw does not ship first-party Agent2Agent (A2A) protocol support. Community-built plugins (e.g. an A2A v0.3.0 gateway plugin) let OpenClaw agents discover and communicate with other A2A-compliant agents, but this is a third-party addition, not a built-in core feature.. A GitHub feature request for native A2A support exists on the openclaw/openclaw repo. A2A capability is provided only through separately maintained community plugins.
Loop / iteration block
No: neither the core agent loop nor the optional Lobster workflow shell has a dedicated for-each/while loop container. Lobster's own maintainers describe its steps as executing strictly top to bottom with no way to jump back to a previous step, and a GitHub feature-request proposal for adding loop/flow-control (a next field enabling backward jumps and max_iterations) is not yet implemented.. Lobster documents only run/command, pipeline, and approval step types plus a boolean condition gate. A maintainer-filed proposal (openclaw/lobster issue #38) states plainly that "steps execute top to bottom. There's no way to jump back to a previous step" and lists step flow control/loops as a future addition, not a shipped feature.
Integrations
Integrations
302 blocks, ~3,900 tool actions302 first-party blocks, ~3,900 underlying tool actions. Sim's landing page cites "1,000+ integrations," a broader figure counting individual API actions rather than top-level blocks. Both numbers describe the same integration surface.
22+ channels, 60,000+ Skills, plus MCP servers22+ native messaging channels plus 60,000+ community-built Skills and MCP access to the broader MCP server ecosystem. Native channel integrations (WhatsApp, Telegram, Slack, Discord, Signal, iMessage, Microsoft Teams, and more) are documented directly. ClawHub's live registry separately lists over 60,000 community-built skills (56,000+ certified), and MCP support adds access to hundreds of third-party MCP servers on top of that.
Trigger types
Webhook, cron, chat, REST API, triggers for 61 appsWebhook, schedule/cron, chat, REST API, and event-based triggers for 61 apps (Slack, Gmail, GitHub, Stripe, etc.)
Chat messages and cron schedules; no generic webhook triggerInbound chat messages on connected channels, and cron-based scheduled jobs (main-session or isolated-session runs); no generic external webhook/event trigger. Cron jobs run agent prompts on a schedule using Croner syntax, with either "main session" delivery (enqueues a system event, optionally wakes the heartbeat) or an isolated dedicated session per run, pruned after a 24-hour retention window by default.
Custom code steps
Yes: the agent can read/write files and run shell commands/scripts directly (subject to exec approval and sandbox policy), rather than through a discrete "code step" primitive in a visual workflow. This is native agent capability (shell exec, file read/write) governed by a three-tier permission system (agent tool allow/deny, sandbox tool filter, exec approvals), not a workflow-builder code block dropped into a defined step sequence.
API publishing
No: there is no mechanism to publish an OpenClaw agent, skill, or automation as a callable REST/webhook API endpoint for external systems to invoke.. OpenClaw is reached through messaging channels or a local Web Control UI, not a deployable API surface. The Gateway itself exposes local control endpoints for its own CLI/UI, not a public API product feature.
SDKs & extensibility
Skill spec, plugin system, and a ~70-repo OSS ecosystemSkill-authoring specification (AgentSkills/SKILL.md) plus a plugin system for channels/providers, and an open-source GitHub organization (~70 repos spanning SDKs, hosted agents, crawlers, and skill registries), not one single unified SDK product. The docs describe skill authoring (frontmatter, gating, tool dispatch), a plugin mechanism used for channels like Matrix/Nostr/Twitch/Zalo, and a broader open-source "federation" of related projects under the openclaw GitHub org.
Publish as MCP server
No first-party feature; only third-party bridge projectsUnknown, not a first-party feature: OpenClaw is documented as an MCP client (consuming external MCP servers), and one third-party community project (openclaw-mcp) provides a bridge exposing an OpenClaw instance itself as an MCP server, but no official OpenClaw feature to publish agent capability as an MCP server exists.. The reverse direction, letting external MCP clients call into OpenClaw, exists only via community-built bridge projects (e.g. a Claude.ai-to-OpenClaw OAuth2 bridge), not as a first-party capability.
Observability & durability
Tracing & observability
Yes: execution logs include a per-block/per-span trace view (duration, cost, token counts, and latency stats like TTFT/TPS) with expandable nested iteration groups, plus a "View Snapshot" frozen copy of the workflow structure and block states at run time for debugging. This trace view is built directly into Sim rather than a raw export browsable in an external tool like Jaeger, and does not expose aggregate latency-percentile charts (p50/p95/p99). The run snapshot serves as a log-detail/debugging artifact rather than a resumable mid-run checkpoint.
Raw JSONL session logs, no dashboard/trace UILocal JSONL session transcripts (per agent, per session) capture the conversation and tool-call history, and a `/subagents` command shows spawned sub-agent status, but there is no customer-facing dashboard or span-level distributed-tracing product. This is raw log-file level detail, not a rendered trace UI.. Transcripts are stored at ~/.openclaw/agents/<agentId>/sessions/*.jsonl with sensitive content redacted by default. Inspecting them means reading the raw file (or building tooling on top), not a built-in visual trace viewer.
Durability & retries
Tool-call retries (up to 10x); single-attempt job orchestrationIndividual tool/API calls have configurable exponential-backoff retry (up to 10 attempts). The background job-orchestration layer itself retries only once by design. Durability instead comes from consecutive-failure tracking on schedules and the human-in-the-loop snapshot pause/resume mechanism. Sim does not offer guaranteed-once-only block execution, a failed-run holding queue for manual recovery, or a "replay a past execution with its original inputs" feature. The per-execution debugging snapshot serves as a log-detail artifact rather than a resumable mid-run checkpoint.
Clean isolated cron runs; no documented retry/checkpoint systemPartial: cron-scheduled jobs run as isolated sessions that start clean and get pruned after a retention window, giving each run a clean, repeatable environment, but there is no automatic retry-with-backoff or checkpoint/replay-of-a-past-run feature for either scheduled jobs or interactive chat sessions.. The cron docs describe delivery diagnostics (intended target, resolved target, fallback delivery used, final delivered state) for message delivery specifically, not a general execution-retry/checkpoint mechanism.
Failure alerting
Delivery diagnostics via chat, no separate alerting featurePartial: cron job runs report delivery diagnostics (whether the agent sent directly, whether fallback delivery was used, the final delivered state) back through the chat channel, but there is no separate proactive alerting mechanism (email/webhook alert on failure or cost/latency threshold).. Failure visibility is folded into the normal chat-delivery flow (the operator sees the delivery outcome in the channel where the job reports), not a distinct alerting/notification product feature.
Data drains
Yes: Enterprise orgs can continuously export workflow logs, job logs, or audit logs on a schedule to a customer-owned S3 bucket, GCS bucket, Azure Blob container, BigQuery table, Snowflake table, Datadog logs intake, or an HTTPS webhook. Each drain exports exactly one data source; multiple drains are created to export multiple sources. Viewing drain config/run history is restricted to org owners/admins.
No: there is no feature to continuously export execution/session data to an external destination (S3, BigQuery, Datadog, webhook, etc). Because all data already lives in local files under the operator's control, any such export would be a user-built script against those local files, not a first-party OpenClaw data-drain feature.. OpenClaw's documentation has no SIEM/export integration comparable to a hosted platform's log-streaming feature.
Async execution
Yes: a workflow can be triggered in fire-and-forget async mode, returning HTTP 202 with a job ID immediately, then polled via a dedicated jobs endpoint through queued/processing/completed/failed states. Async jobs are tracked via polling the job endpoint rather than a completion webhook/callback option.
Yes: generative media tools (image/video/music generation) run asynchronously in the background and post results into the chat session when ready, and cron jobs run independently of any single interactive chat session. Unlike a cloud-hosted platform, the Gateway process itself must remain running on the operator's machine/server for any of this to execute.. This differs from a fully server-hosted workflow platform in one respect: if the machine running the Gateway is off, no async or scheduled execution happens, since there is no separate cloud execution layer independent of the self-hosted process.
Execution limits
5-50 min sync timeout, 90 min async, 15-300 concurrentPlan-gated: synchronous API calls time out at 5 minutes on the free plan and 50 minutes on paid plans, async calls at 90 minutes on every plan, with 15 to 300 concurrent executions per billing entity depending on plan. These limits are not published in docs; request bodies are separately capped at 10 MB.
No fixed platform-wide execution-time or concurrency ceiling is published by OpenClaw itself. Sub-agent nesting is capped at 2 levels deep (depth-2 sessions cannot spawn further sub-agents), and any other limits (request timeouts, rate limits) come from whichever LLM provider API the operator has configured, not from OpenClaw.. Because OpenClaw runs on infrastructure the operator controls, execution-time/concurrency limits are a function of that operator's own hardware and their model provider's API limits, not an OpenClaw-side ceiling.
Partial-failure handling
Implicit isolation via sub-agent sessions, no explicit branching error pathPartial: because sub-agents run in isolated sessions, one sub-agent failing does not halt sibling sub-agents or the main session, an implicit form of failure isolation, but there is no explicit "route this failed step to an error-handling path while the rest of the run continues" mechanism the way a branching workflow builder offers.. Isolation here comes from sub-agent session/sandbox separation by design, not from a dedicated try/catch or conditional-branch construct users configure per step.
Support
Support channels
Community support plus Enterprise 'Dedicated Support'Community (open source, GitHub) plus an unquantified "Dedicated Support" flag on the Enterprise plan. Enterprise and pricing pages do not include CSM, onboarding/enablement, or professional-services details beyond a plan-comparison-table "Dedicated Support" flag.
Docs, GitHub issues, community; no paid vendor support deskCommunity-driven support via official documentation, the GitHub repository/issue tracker, and the broader OpenClaw ecosystem/community channels; no dedicated paid vendor support desk, since no vendor sells a support contract.. The project is community-maintained under Foundation governance; support is the standard open-source model of docs, GitHub issues, and community discussion rather than a ticketed enterprise support line.
SLA
No SLA (self-hosted community project)Not publicly documented. No SLA is published, typical for free, self-hosted, community-governed open-source software with no vendor-operated service to guarantee uptime for.
Community
100,000+ buildersOver 100,000 builders use Sim
~382,000 GitHub stars, extremely rapid growth since Nov 2025Large and very fast-growing: the GitHub repository has roughly 382,000 stars, reported by multiple sources as the fastest-growing and, by some accounts, most-starred non-aggregator open-source project in GitHub's history, alongside an active ClawHub skill-sharing community.. Growth milestones include 9,000 stars in the first 24 hours after launch (as Clawdbot, November 2025) and 247,000+ stars by March 2, 2026. Star counts fluctuate and are best checked live on the GitHub repository.
Academy / training
No: OpenClaw has no structured courses, certification program, or formal academy. Learning resources are the official documentation site (docs.openclaw.ai), the GitHub repository, and third-party community blog posts/guides, not a vendor-run curriculum.. No certification or structured learning-path product exists on official OpenClaw sources, consistent with it being a community open-source project rather than a vendor with a dedicated training business line.
Sim standout features
AI Copilot / Chat agent-building surface
Chat and in-editor Copilot suggest and build workflow changes directly.
A natural-language surface (Chat) and in-editor Copilot that can explain, suggest, and build workflow changes directly, backed by a dedicated copilot module with its own tool registry.Hybrid semantic + keyword knowledge base
Combines vector and full-text search with configurable chunking across 11 file formats.
Built-in RAG with pgvector embeddings and a generated tsvector column for combined vector + full-text search, plus a token-based chunker with configurable chunk size/overlap and 11 supported file formats (csv, doc, docx, html, json, md, pdf, pptx, txt, xlsx, yaml).Native MCP client and server
Call external MCP servers as tools, or expose Sim workflows as an MCP server.
A dedicated MCP block lets any workflow call external MCP servers as a tool, and a serve/workflow-servers API surface lets Sim expose its own workflows as MCP servers.Fork a workspace into dev, qa, and prod environments
Fork, diff, and promote environments with mandatory credential remapping.
Fork a whole workspace into a dev/qa/prod-style child environment, preview a diff, and promote changes bidirectionally. Credential and env-var remapping is required on every promote, so secrets never cross environments silently.Human-in-the-loop approvals with durable resume
Pause a run for human approval and resume later via a durable snapshot link.
A dedicated block pauses a run and waits for a human-submitted approval form, backed by persisted execution snapshots so the run can resume later via a link, even after a server restart.Self-hostable under Apache 2.0
Fully open source with Docker Compose and Helm deployment options.
Fully open source (Apache 2.0), with Docker Compose files and a Helm chart for Kubernetes deployment, alongside a managed cloud-hosted option.Documented OpenClaw limitations
Single-operator trust model. No multi-user RBAC or org-level admin controls
Designed for one trusted operator per install, not multi-user org admin controls.
OpenClaw's security documentation states its design assumes "one trusted operator boundary per gateway (single-user, personal-assistant model)," not hostile multi-tenant isolation. There is no role-based access control, org/team admin console, or per-user permission model comparable to a team collaboration platform.ClawHub marketplace has documented, ongoing supply-chain security incidents
Researchers found hundreds of ClawHub skills leaking credentials or containing malware.
Researchers found 283 ClawHub skills (roughly 7.1% of the registry at the time) leaking API keys and other credentials, and a separate scan identified 24 accounts distributing over 600 malicious skills before scanning was introduced. OpenClaw has since added VirusTotal and SkillSpector scanning, but its documentation still tells users to "treat third-party skills as untrusted code."No deployable API/webhook endpoint or visual workflow builder
No feature to publish an agent or automation as a callable API/webhook endpoint.
OpenClaw is a chat-interface agent gateway, not a workflow/automation platform. It has no feature to publish a configured agent, skill, or automation as a callable REST/webhook endpoint for external systems, and no drag-and-drop canvas for composing multi-step logic.No enterprise compliance certifications (SOC 2, ISO 27001, HIPAA)
No SOC 2/ISO/HIPAA attestations; the self-hosting operator owns all compliance risk.
OpenClaw is a self-hosted open-source project run by a non-profit foundation, not a vendor selling a hosted service, so it publishes no SOC 2, ISO 27001, HIPAA, or similar compliance attestation. Security for data-at-rest and processing falls entirely on the operator running their own instance.Rapid rebranding and name churn created real confusion and scam risk
Three name changes in about ten weeks, including an Anthropic trademark dispute, fueled scam activity.
The project launched in November 2025 as "Warelay," was renamed to "Clawdbot," then to "Moltbot" on January 27, 2026 after an Anthropic trademark complaint over similarity to "Claude," then to "OpenClaw" three days later. Coverage from the period documents scam and impersonation activity, including a reported $16M crypto scam, riding the confusion.Bottom line
Choose Sim if you want an open-source, self-hostable AI workspace that treats AI agents as first-class citizens: native multi-LLM support, real-time multiplayer editing, environment promotion (dev/qa/prod), human-in-the-loop approvals, and enterprise governance (SSO, credential-level permissions, audit logs) built in rather than bolted on.
Choose OpenClaw if you specifically need 22+ messaging channels as the native interface: OpenClaw ships a multi-channel inbox connecting one assistant to WhatsApp, Telegram, Slack, Discord, Google Chat, Signal, iMessage, Microsoft Teams, IRC, Matrix, Feishu, LINE, Mattermost, Nextcloud Talk, and more. Users talk to the same agent from whichever chat app they already use, not a dedicated web builder UI.
Frequently asked questions
Sim is an open-source AI workspace where teams build, deploy, and manage AI agents visually, conversationally, or with code. OpenClaw is a free, open-source, self-hosted personal AI agent that runs on a user's own machine or server and connects to messaging platforms (WhatsApp, Telegram, Slack, Discord, Signal, iMessage, Microsoft Teams, and others) as its primary interface, extensible via a Skills plugin system and the ClawHub marketplace. It is not a visual workflow/automation builder like Sim, n8n, or Power Automate. Teams considering a switch typically weigh licensing (Sim is Apache 2.0 and self-hostable), pricing model, and how AI-native the platform's agent-building experience is.