FastMCP uses the function's type hints and docstring to build the tool schema automatically. The parameter name becomes the JSON Schema key, the type hint determines the schema type, and the docstring becomes the tool description. No manual schema writing.
Connecting to Claude Desktop
Add this to your claude_desktop_config.json:
{"mcpServers":{"mini-tools":{"command":"python","args":["/absolute/path/to/server.py"]}}}
Restart Claude Desktop. The /read_file and /fetch_url commands appear immediately. Claude can inspect local files and pull live web data through your custom tools.
Connecting to other platforms
Any platform that supports the MCP protocol can consume your server. The transport is stdio — the platform spawns your process and communicates over stdin/stdout. No HTTP endpoints, no webhooks, no API keys to rotate.
Platforms like Nebula let you register MCP tools as agent skills. Your server registers tools, and Nebula's agent runtime discovers them automatically — no per-tool configuration needed.
What to build next
-
SQLite MCP server — let agents query your local database
-
GitHub MCP server — expose repo operations as tools
-
Slack MCP server — let agents search messages and post updates
-
CLI wrapper MCP server — wrap any command-line tool as an MCP tool
The MCP protocol makes tool-building boring in the best sense. One file, typed functions, and your AI agent just gained a capability it didn't have before. That's the whole idea.