No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by freema · MCP Server · ★ 184
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openclaw-mcp safe to install? View the security audit →
OpenClaw MCP Server 🦞 Model Context Protocol (MCP) server for OpenClaw AI assistant integration. Demo Why I Built This 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? Quick Start Docker (Recommended) Pre-built images are published to GitHub Container Registry o
| Stars | 184 |
| Forks | 25 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 76.3885794718681/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-19 |
| Created | 2026-02-02 |
| Platforms | claude-code, docker, mcp, node |
| Est. Tokens | ~15k |
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openclaw-mcp is 🦞 MCP server for OpenClaw - secure bridge between Claude.ai and your self-hosted OpenClaw assistant with OAuth2 authentication. It is categorized as a MCP Server with 184 GitHub stars.
openclaw-mcp is primarily written in TypeScript. It covers topics such as docker-compose, mcp-server, open-claw.
You can find installation instructions and usage details in the openclaw-mcp GitHub repository at github.com/freema/openclaw-mcp. The project has 184 stars and 25 forks, indicating an active community.
openclaw-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openclaw-mcp on Agent Skills Hub include toolhive-studio, mcp-shodan, flow-like. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: