Skip to content
MCP Server Directory logo
developer-tools

Openclaw Mcp Servers

49 AI tools across 9 MCP servers. Enterprise AGI Runtime (1,054 tests). Free tier. ☕ buymeacoffee.com/yesinyagami

Reviewed overview

MCP 服务器概览

What is OpenClaw MCP Servers? OpenClaw MCP Servers is a collection of 9 production MCP (Model Context Protocol) servers and an ecosystem of AI tooling (49+ AI tools) designed to run multi-brain AI workloads (Claude, Cursor, and custom agents) at edge scale. It provides prebuilt servers for security scanning, knowledge graph/GraphRAG, compliance checking, finance tests, memory systems, analytics, content generation, webhook ingestion and an API gateway.

How to use the project?

  • Browse or clone the GitHub repo: https://github.com/yedanyagamiai-cmd/openclaw-mcp-servers
  • Deploy the provided Cloudflare Workers (229+ edge workers) or run locally following the repo instructions (TypeScript-based).
  • Configure your model/backends (Claude, Cursor, custom brains) and data stores (D1 tables) and enable the MCP servers you need.
  • Use the free tier to start; commercial products (MCP Starter Kit, AGI Playbook, consulting, security audits) are available if you need packaged deployments or professional services.

Key features

  • 9 ready-made MCP servers (Security Scanner, Knowledge Graph, Compliance, Finance, Memory, Analytics, Content, Webhook, API Gateway).
  • Edge-first deployment: 229+ Cloudflare Workers / global edge.
  • Persistent storage: 54 D1 database tables with constraints.
  • Multi-brain architecture: 7-brain cluster combining Claude + several custom brains.
  • Constitutional Policy Engine with safety rules (NEVER/ALWAYS constraints).
  • Extensive testing: over 1,000 automated tests across systems.
  • Products & support: AGI Playbook, MCP Starter Kit, security audits, paid consulting; donation/support links (Ko-fi, Lemon Squeezy).

Typical use cases

  1. Automated OWASP-style security audits using an Agentic AI scanner.
  2. Building GraphRAG knowledge systems and enterprise Knowledge Graphs.
  3. EU AI Act / regulatory compliance checking workflows.
  4. Finance testing and FinanceOS integrations.
  5. Long-term memory and context management for multi-agent systems.
  6. Real-time analytics and observability for AI services.
  7. AI-driven content generation and centralized webhook ingestion.
  8. Routing & orchestration of multiple LLMs/agents via an API gateway.

FAQ

  • Is there a free tier?

Yes — the project advertises a free tier and relies on Cloudflare Workers for a free/edge-friendly deployment path.

  • Which models and agents are supported?

Designed to work with Claude, Cursor and custom agent brains (multi-brain cluster). The repo shows integration points for model context protocol (MCP).

  • What stack and languages are used?

Primarily TypeScript and Cloudflare Workers, with D1 database tables for storage.

  • How mature/stable is it?

The project advertises production-ready servers, a constitutional safety engine, and 1k+ tests passing. Check the repo and CI/tests for current passing status.

  • Where can I get support or commercial services?

Support and paid products are available via Lemon Squeezy and Ko-fi links in the project. Consulting and security audits are offered.

  • How do I deploy it?

Follow the repository README for deployment steps: configure Cloudflare Workers, provision D1 tables, set model/back-end credentials and enable the MCP servers you need. For turnkey options, consider the MCP Starter Kit or paid consulting.