openclaw — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited openclaw (Plugin) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<!-- mcp-name: io.github.freema/openclaw-mcp -->
<a href="https://glama.ai/mcp/servers/@freema/openclaw-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@freema/openclaw-mcp/badge" /> </a>
🦞 Model Context Protocol (MCP) server for OpenClaw AI assistant integration.
<p align="center"> <img src="docs/assets/claude-ai-demo.gif" alt="OpenClaw MCP in Claude.ai" width="720" /> </p>
Hey! I created this MCP server because I didn't want to rely solely on messaging channels to communicate with OpenClaw. What really excites me is the ability to connect OpenClaw to the Claude web UI. Essentially, my chat can delegate tasks to my Claw bot, which then handles everything else — like spinning up Claude Code to fix issues for me.
Think of it as an AI assistant orchestrating another AI assistant. Pretty cool, right?
Pre-built images are published to GitHub Container Registry on every release.
docker pull ghcr.io/freema/openclaw-mcp:latestCreate a docker-compose.yml:
services:
mcp-bridge:
image: ghcr.io/freema/openclaw-mcp:latest
container_name: openclaw-mcp
restart: unless-stopped
ports:
- "3000:3000"
environment:
- OPENCLAW_URL=http://host.docker.internal:18789
- OPENCLAW_GATEWAY_TOKEN=${OPENCLAW_GATEWAY_TOKEN}
- OPENCLAW_MODEL=openclaw
- AUTH_ENABLED=true
- MCP_CLIENT_ID=openclaw
- MCP_CLIENT_SECRET=${MCP_CLIENT_SECRET}
- MCP_ISSUER_URL=${MCP_ISSUER_URL:-}
- TRUST_PROXY=1
- CORS_ORIGINS=https://claude.ai
extra_hosts:
- "host.docker.internal:host-gateway"
read_only: true
security_opt:
- no-new-privilegesGenerate secrets and start:
export MCP_CLIENT_SECRET=$(openssl rand -hex 32)
export OPENCLAW_GATEWAY_TOKEN=your-gateway-token
docker compose up -dThen in Claude.ai add a custom MCP connector pointing to https://your-domain.com/mcp with MCP_CLIENT_ID=openclaw and your MCP_CLIENT_SECRET.
Important: The connector URL must end with `/mcp` — that's the Streamable HTTP endpoint. A bare domain (https://your-domain.com) hits the server root and returns 404 after OAuth completes.Tip: Pin a specific version instead oflatestfor production:ghcr.io/freema/openclaw-mcp:1.1.0
npx openclaw-mcpAdd to your Claude Desktop config:
{
"mcpServers": {
"openclaw": {
"command": "npx",
"args": ["openclaw-mcp"],
"env": {
"OPENCLAW_URL": "http://127.0.0.1:18789",
"OPENCLAW_GATEWAY_TOKEN": "your-gateway-token",
"OPENCLAW_MODEL": "openclaw",
"OPENCLAW_TIMEOUT_MS": "300000"
}
}
}
}AUTH_ENABLED=true MCP_CLIENT_ID=openclaw MCP_CLIENT_SECRET=your-secret \
MCP_ISSUER_URL=https://mcp.your-domain.com \
CORS_ORIGINS=https://claude.ai OPENCLAW_GATEWAY_TOKEN=your-gateway-token \
npx openclaw-mcp --transport http --port 3000Important: When running behind a reverse proxy (Caddy, nginx, Traefik, Cloudflare Tunnel, etc.) you must set: -MCP_ISSUER_URL(or--issuer-url) to your public HTTPS URL — otherwise OAuth metadata advertiseshttp://localhost:3000and clients fail to authenticate. -TRUST_PROXY=1(or--trust-proxy 1) — otherwiseexpress-rate-limitrejects the proxy'sX-Forwarded-Forheader and/tokencrashes withERR_ERL_UNEXPECTED_X_FORWARDED_FOR.
See Installation Guide for details.
┌─────────────────────────────────────────────────────────────────┐
│ Your Server │
│ │
│ ┌─────────────────┐ ┌─────────────────────────┐ │
│ │ OpenClaw │ │ OpenClaw MCP │ │
│ │ Gateway │◄────►│ Bridge Server │ │
│ │ :18789 │ │ :3000 │ │
│ │ │ │ │ │
│ │ OpenAI-compat │ │ - OAuth 2.1 auth │ │
│ │ /v1/chat/... │ │ - CORS protection │ │
│ └─────────────────┘ │ - Input validation │ │
│ └──────────┬──────────────┘ │
│ │ │
└──────────────────────────────────────┼──────────────────────────┘
│ HTTPS + OAuth 2.1
▼
┌─────────────────┐
│ Claude.ai │
│ (MCP Client) │
└─────────────────┘| Tool | Description |
|---|---|
openclaw_chat | Send messages to OpenClaw and get responses |
openclaw_status | Check OpenClaw gateway health |
openclaw_instances | List all configured OpenClaw instances |
| Tool | Description |
|---|---|
openclaw_chat_async | Queue a message, get task_id immediately |
openclaw_task_status | Check task progress and get results |
openclaw_task_list | List all tasks with filtering |
openclaw_task_cancel | Cancel a pending task |
Orchestrate multiple OpenClaw gateways from a single MCP server. One bridge, many claws — route requests to prod, staging, dev, or whatever you name them (lobster-supreme and the-claw-abides are perfectly valid names).
┌──────────────────────────────────────────────────────────────────────┐
│ Claude.ai / Claude Desktop │
│ (MCP Client) │
└──────────────────────┬───────────────────────────────────────────────┘
│
▼
┌──────────────────────────────────────────────────────────────────────┐
│ OpenClaw MCP Bridge Server │
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Instance │ │ Instance │ │ Instance │ │
│ │ Registry │ │ Resolver │ │ Validator │ │
│ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │
│ │ │ │ │
│ ┌──────┴─────────────────┴──────────────────┴───────┐ │
│ │ Per-Instance OpenClaw Clients │ │
│ │ (separate auth, timeout, URL per instance) │ │
│ └────────┬──────────────┬──────────────┬────────────┘ │
└───────────┼──────────────┼──────────────┼────────────────────────────┘
│ │ │
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ 🦞 prod │ │ 🦞 staging │ │ 🦞 dev │
│ (default) │ │ │ │ │
│ :18789 │ │ :18789 │ │ :18789 │
│ OpenClaw GW │ │ OpenClaw GW │ │ OpenClaw GW │
└──────────────┘ └──────────────┘ └──────────────┘OPENCLAW_INSTANCES='[
{"name": "prod", "url": "http://prod:18789", "token": "tok1", "default": true},
{"name": "staging", "url": "http://staging:18789", "token": "tok2"},
{"name": "dev", "url": "http://dev:18789", "token": "tok3"}
]'All tools accept an optional instance parameter to target a specific gateway:
# Chat with staging instance
openclaw_chat message="Deploy status?" instance="staging"
# Check health of prod
openclaw_status instance="prod"
# List all configured instances
openclaw_instances
# Async task targeting dev
openclaw_chat_async message="Run tests" instance="dev"When instance is omitted, the default instance is used. Each instance has its own auth token, timeout, and URL — fully isolated.
openclaw_instancesSee Configuration — Multi-Instance Mode for the full reference.
⚠️ Always enable authentication in production!
# Generate secure client secret
export MCP_CLIENT_SECRET=$(openssl rand -hex 32)
# Run with auth enabled
AUTH_ENABLED=true MCP_CLIENT_ID=openclaw MCP_CLIENT_SECRET=$MCP_CLIENT_SECRET \
openclaw-mcp --transport httpConfigure CORS to restrict access:
CORS_ORIGINS=https://claude.ai,https://your-app.comSee Configuration for all security options.
Starting with v1.5.0, the primary transport is Streamable HTTP (--transport http). The legacy SSE transport (--transport sse) is deprecated but still works for backward compatibility.
| Before | After |
|---|---|
--transport sse | --transport http (recommended) |
Primary endpoint: GET /sse | Primary endpoint: POST/GET/DELETE /mcp |
Health: "transport": "sse" | Health: "transport": "streamable-http" |
--transport sse with --transport http # Before
openclaw-mcp --transport sse --port 3000
# After
openclaw-mcp --transport http --port 3000/mcp (Streamable HTTP)/sse and /messages endpoints still work. A deprecation warning is logged on each SSE connection.Note: --transport sse will continue to work as a deprecated alias. Both transports are served simultaneously regardless of which flag you use. // openclaw.json
{ "gateway": { "http": { "endpoints": { "chatCompletions": { "enabled": true } } } } }MIT
Created by Tomáš Grasl
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.