{
    "name": "fastmcp",
    "version": "1.0.0",
    "description": "Build, test, and deploy Python MCP servers.",
    "system_prompt": "name fastmcp description Build, test, and deploy Python MCP servers. version 1.0.0 author Hermes Agent license MIT platforms [\"linux\",\"macos\",\"windows\"] metadata {\"hermes\":{\"tags\":[\"MCP\",\"FastMCP\",\"Python\",\"Tools\",\"Resources\",\"Prompts\",\"Deployment\"],\"homepage\":\"https://gofastmcp.com\",\"related_skills\":[\"hermes-agent\",\"mcporter\"]}} prerequisites {\"commands\":[\"python\"]} FastMCP Build MCP servers in Python with FastMCP, validate them locally, install them into MCP clients, and deploy them as HTTP endpoints. When to Use Use this skill when the task is to: create a new MCP server in Python wrap an API, database, CLI, or file-processing workflow as MCP tools expose resources or prompts in addition to tools smoke-test a server with the FastMCP CLI before wiring it into Hermes or another client install a server into Claude Code, Claude Desktop, Cursor, or a similar MCP client prepare a FastMCP server repo for HTTP deployment Use native-mcp when the server already exists and only needs to be connected to Hermes. Use mcporter when the goal is ad-hoc CLI access to an existing MCP server instead of building one. Prerequisites Install FastMCP in the working environment first: pip install fastmcp fastmcp version For the API template, install httpx if it is not already present: pip install httpx Included Files Templates templates/api_wrapper.py - REST API wrapper with auth header support templates/database_server.py - read-only SQLite query server templates/file_processor.py - text-file inspection and search server Scripts scripts/scaffold_fastmcp.py - copy a starter template and replace the server name placeholder References references/fastmcp-cli.md - FastMCP CLI workflow, installation targets, and deployment checks Workflow 1. Pick the Smallest Viable Server Shape Choose the narrowest useful surface area first: API wrapper: start with 1-3 high-value endpoints, not the whole API database server: expose read-only introspection and a constrained query path file processor: expose deterministic operations with explicit path arguments prompts/resources: add only when the client needs reusable prompt templates or discoverable documents Prefer a thin server with good names, docstrings, and schemas over a large server with vague tools. 2. Scaffold from a Template Copy a template directly or use the scaffold helper: python ~/.hermes/skills/mcp/fastmcp/scripts/scaffold_fastmcp.py \\ --template api_wrapper \\ --name \"Acme API\" \\ --output ./acme_server.py Available templates: python ~/.hermes/skills/mcp/fastmcp/scripts/scaffold_fastmcp.py --list If copying manually, replace __SERVER_NAME__ with a real server name. 3. Implement Tools First Start with @mcp.tool functions before adding resources or prompts. Rules for tool design: Give every tool a concrete verb-based name Write docstrings as user-facing tool descriptions Keep parameters explicit and typed Return structured JSON-safe data where possible Validate unsafe inputs early Prefer read-only behavior by default for first versions Good tool examples: get_customer search_tickets describe_table summarize_text_file Weak tool examples: run process do_thing 4. Add Resources and Prompts Only When They Help Add @mcp.resource when the client benefits from fetching stable read-only content such as schemas, policy docs, or generated reports. Add @mcp.prompt when the server should provide a reusable prompt template for a known workflow. Do not turn every document into a prompt. Prefer: tools for actions resources for data/document retrieval prompts for reusable LLM instructions 5. Test the Server Before Integrating It Anywhere Use the FastMCP CLI for local validation: fastmcp inspect acme_server.py:mcp fastmcp list acme_server.py --json fastmcp call acme_server.py search_resources query=router limit =5 --json For fast iterative debugging, run the server locally: fastmcp run acme_server.py:mcp To test HTTP transport locally: fastmcp run acme_server.py:mcp --transport http --host 127.0.0.1 --port 8000 fastmcp list http://127.0.0.1:8000/mcp --json fastmcp call http://127.0.0.1:8000/mcp search_resources query=router --json Always run at least one real fastmcp call against each new tool before claiming the server works. 6. Install into a Client When Local Validation Passes FastMCP can register the server with supported MCP clients: fastmcp install claude-code acme_server.py fastmcp install claude-desktop acme_server.py fastmcp install cursor acme_server.py -e . Use fastmcp discover to inspect named MCP servers already configured on the machine. When the goal is Hermes integration, either: configure the server in ~/.hermes/config.yaml using the native-mcp skill, or keep using FastMCP CLI commands during development until the interface stabilizes 7. Deploy After the Local Contract Is Stable For managed hosting, Prefect Horizon is the path FastMCP documents most directly. Before deployment: fastmcp inspect acme_server.py:mcp Make sure the repo contains: a Python file with the FastMCP server object requirements.txt or pyproject.toml any environment-variable documentation needed for deployment For generic HTTP hosting, validate the HTTP transport locally first, then deploy on any Python-compatible platform that can expose the server port. Common Patterns API Wrapper Pattern Use when exposing a REST or HTTP API as MCP tools. Recommended first slice: one read path one list/search path optional health check Implementation notes: keep auth in environment variables, not hardcoded centralize request logic in one helper surface API errors with concise context normalize inconsistent upstream payloads before returning them Start from templates/api_wrapper.py . Database Pattern Use when exposing safe query and inspection capabilities. Recommended first slice: list_tables describe_table one constrained read query tool Implementation notes: default to read-only DB access reject non- SELECT SQL in early versions limit row counts return rows plus column names Start from templates/database_server.py . File Processor Pattern Use when the server needs to inspect or transform files on demand. Recommended first slice: summarize file contents search within files extract deterministic metadata Implementation notes: accept explicit file paths check for missing files and encoding failures cap previews and result counts avoid shelling out unless a specific external tool is required Start from templates/file_processor.py . Quality Bar Before handing off a FastMCP server, verify all of the following: server imports cleanly fastmcp inspect <file.py:mcp> succeeds fastmcp list <server spec> --json succeeds every new tool has at least one real fastmcp call environment variables are documented the tool surface is small enough to understand without guesswork Troubleshooting FastMCP command missing Install the package in the active environment: pip install fastmcp fastmcp version fastmcp inspect fails Check that: the file imports without side effects that crash the FastMCP instance is named correctly in <file.py:object> optional dependencies from the template are installed Tool works in Python but not through CLI Run: fastmcp list server.py --json fastmcp call server.py your_tool_name --json This usually exposes naming mismatches, missing required arguments, or non-serializable return values. Hermes cannot see the deployed server The server-building part may be correct while the Hermes config is not. Load the native-mcp skill and configure the server in ~/.hermes/config.yaml , then restart Hermes. References For CLI details, install targets, and deployment checks, read references/fastmcp-cli.md .",
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