# mcp-knowledge-base MCP server Example MCP server to call command line apps ## Components ### Tools The server implements one tool: - run_command: Runs a command line comment - Takes "cmd" and "args" as string arguments - Runs the command and returns stdout, stderr, status_code, etc. ## Configuration ## Quickstart ### Install #### Claude Desktop On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json` On Windows: `%APPDATA%/Claude/claude_desktop_config.json`
Development/Unpublished Servers Configuration ``` "mcpServers": { "mcp-knowledge-base": { "command": "uv", "args": [ "--directory", "/Users/$(whoami)/experiments/claude-mvp/mcp-knowledge-base", "run", "mcp-knowledge-base" ] } } ```
Published Servers Configuration ``` "mcpServers": { "mcp-knowledge-base": { "command": "uvx", "args": [ "mcp-knowledge-base" ] } } ```
## Development ### Building and Publishing To prepare the package for distribution: 1. Sync dependencies and update lockfile: ```bash uv sync ``` 2. Build package distributions: ```bash uv build ``` This will create source and wheel distributions in the `dist/` directory. 3. Publish to PyPI: ```bash uv publish ``` Note: You'll need to set PyPI credentials via environment variables or command flags: - Token: `--token` or `UV_PUBLISH_TOKEN` - Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD` ### Debugging Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector). You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command: ```bash npx @modelcontextprotocol/inspector uv --directory /Users/markus/experiments/claude-mvp/mcp-knowledge-base run mcp-knowledge-base ``` Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.