awesome-openclaw

Awesome OpenClaw is a curated catalog focused on the OpenClaw ecosystem, providing a centralized reference for frameworks, skills, tooling, deployments, and real-world use cases. In an MCP context this repository acts as a data source and discovery endpoint for developers building OpenClaw agents, plugins, and integrations. The available material helps you understand how to connect agents to tools and resources, discover official resources, and explore curated collections and community-driven content. Use the MCP tooling to fetch, index, and query the catalog, then integrate relevant items (skills, plugins, or deployments) into your own agent workflows or runtimes. The emphasis is on discoverability, interoperability, and staying aligned with OpenClaw’s official resources and curated community content.

Prerequisites:

• Git installed on your system
• Access to a compatible MCP runtime or server (per your environment)
• Optional: Docker if you prefer containerized setup

Step-by-step:

1. Clone this repository locally: git clone https://github.com/vincentkoc/awesome-openclaw.git cd awesome-openclaw

2. Review the MCP server configuration (mcp_config) in this repo. This example uses a placeholder server definition since this repository is a curated content source rather than a running MCP server.

3. If you already have an MCP runtime, ensure it is up and running. Typical steps involve starting the MCP server with your preferred runtime, for example:

   • Node-based runtimes: npm install && node path/to/server.js
   • Python-based runtimes: python -m your_mcp_runtime
   • Docker: docker run -i your-mcp-runtime-image

4. Create or adapt an mcp_config.json for your environment. A minimal configuration that registers your server (as a catalog source) might look like: { "mcpServers": { "awesome-openclaw": { "command": "your-runtime-command", "args": ["path/to/server.js"] } } } Save this as mcp_config.json and point your MCP runtime to it.

5. Run the MCP runtime with the configuration. Ensure any required environment variables are set as documented by your MCP runtime. Validate that you can query the catalog and fetch items from theAwesome OpenClaw dataset.

6. Optional: If you prefer containerized deployment, build or pull a container image that includes your MCP runtime and the mcp_config.json, then run it via Docker.

Prerequisites recap: Git, a compatible MCP runtime (Node, Python, or Docker-based), and network access to fetch dependencies or assets as needed.

Notes and tips:

• This repository is a curated content source for OpenClaw-related resources. It does not itself provide a running MCP server by default, so your MCP setup will need to point to this data source as a catalog.
• If you publish your own MCP server that serves this catalog, ensure the mcp_config.json aligns with the runtime's expected format (commands and arguments).
• Consider adding environment variables for authentication, rate limiting, or cache behavior in your MCP runtime to optimize catalog queries.
• When integrating with OpenClaw ecosystems, prefer official resources and maintainers’ guidance to ensure compatibility with plugin and skill registries.
• If you encounter issues fetching data, verify that the catalog index endpoints or file paths used by your MCP runtime are accessible and that any CORS or network restrictions are properly configured.