ai.smithery/FelixYifeiWang-felix-mcp-smithery

# Felix MCP (Smithery)

A tiny Model Context Protocol server with a few useful tools, deployed on Smithery, tested in Claude Desktop, and indexed in NANDA.

Tools included

• hello(name) – quick greeting
• randomNumber(max?) – random integer (default 100)
• weather(city) – current weather via wttr.in
• summarize(text, maxSentences?, model?) – OpenAI-powered summary (requires OPENAI_API_KEY)

Public server page https://smithery.ai/server/@FelixYifeiWang/felix-mcp-smithery

MCP endpoint (streamable HTTP) https://server.smithery.ai/@FelixYifeiWang/felix-mcp-smithery/mcp (In Smithery/NANDA, auth is attached via query param api_key and optional profile, configured in the platform UI; do not hardcode secrets here.)

Demo

In Claude Desktop (recommended)

1. Open Settings → Developer → mcpServers and add:

    {
      "mcpServers": {
        "felix-mcp-smithery": {
          "command": "npx",
          "args": [
            "-y",
            "@smithery/cli@latest",
            "run",
            "@FelixYifeiWang/felix-mcp-smithery",
            "--key",
            "YOUR_SMITHERY_API_KEY",
            "--profile",
            "YOUR_PROFILE_ID"
          ]
        }
      }
    }

2. Start a new chat and run:
   • “List tools from felix-mcp-smithery”
   • “Call hello with { "name": "Felix" }”
   • “Call summarize on this text (2 sentences): …”

Features

• Streamable HTTP MCP – Express + MCP SDK’s StreamableHTTPServerTransport on /mcp (POST/GET/DELETE).
• Session-aware – proper handling of Mcp-Session-Id (no close recursion).
• OpenAI summarization – tidy summaries via chat completions (model default gpt-4o-mini).
• Zero-friction hosting – packaged as a container and deployed on Smithery.

Install (local)

Requires Node 18+ (tested on Node 20).

git clone https://github.com/FelixYifeiWang/felix-mcp-smithery
cd felix-mcp-smithery
npm install

Set env (only needed if you’ll call summarize locally):

export OPENAI_API_KEY="sk-..."

Run:

node index.js
# ✅ MCP Streamable HTTP server on 0.0.0.0:8081 (POST/GET/DELETE /mcp)

Local curl:

curl -s -X POST "http://localhost:8081/mcp" \
  -H 'Content-Type: application/json' \
  -H 'Mcp-Protocol-Version: 2025-06-18' \
  --data '{"jsonrpc":"2.0","id":0,"method":"initialize","params":{"protocolVersion":"2025-06-18"}}'

Usage (tools)

hello

{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"hello","arguments":{"name":"Felix"}}}

randomNumber

{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"randomNumber","arguments":{"max":10}}}

weather

{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"weather","arguments":{"city":"Boston"}}}

summarize (needs OPENAI_API_KEY set on the server)

{"jsonrpc":"2.0","id":4,"method":"tools/call","params":{"name":"summarize","arguments":{"text":"(paste long text)","maxSentences":2}}}

How it works

• Server core: McpServer from @modelcontextprotocol/sdk with tools registered in buildServer(). Transport: StreamableHTTPServerTransport on /mcp handling:
  • POST /mcp — JSON-RPC requests (and first-time initialize)
  • GET /mcp — server-to-client notifications (SSE)
  • DELETE /mcp — end session
• CORS: Allows all origins; exposes Mcp-Session-Id header (good for hosted clients).
• OpenAI summarize: Thin fetch wrapper around /v1/chat/completions with a short “crisp summarizer” system prompt.

Deployment (Smithery)

1. GitHub repo with:
   • index.js (Express + MCP)
   • package.json (@modelcontextprotocol/sdk, express, cors, zod)
   • Dockerfile
   • smithery.yaml:

     kind: server
     name: felix-mcp-smithery
     version: 1.0.0
     runtime: container
     
     startCommand:
       type: http
     
     transport: streamable-http
     port: 8081
     path: /mcp
     ssePath: /mcp
     health: /

2. In Smithery:
   • Create server from the repo.
   • Add Environment Variables: OPENAI_API_KEY (optional for summarize).
   • Deploy → confirm logs show: ✅ MCP Streamable HTTP server on 0.0.0.0:8081 (POST/GET/DELETE /mcp)

NANDA Index

• Go to join39.org → Context Agents → Add
  • Agent Name: Felix MCP (Smithery)
  • MCP Endpoint: https://server.smithery.ai/@FelixYifeiWang/felix-mcp-smithery/mcp?api_key=YOUR_KEY&profile=YOUR_PROFILE
  • Description: Streamable-HTTP MCP hosted on Smithery. Tools: hello, randomNumber, weather, summarize (OpenAI).
• Test from NANDA: initialize → tools/list → call hello.

Project structure

.
├─ index.js            # Express + Streamable HTTP + tools
├─ package.json        # sdk/express/cors/zod
├─ Dockerfile          # container build for Smithery
└─ smithery.yaml       # Smithery project config

Assignment rubric mapping

• ✅ Find/Build: Custom MCP server with 4 tools
• ✅ Deploy: Hosted on Smithery (public server page linked)
• ✅ Test in a host: Verified in Claude Desktop (screenshots/recording included)
• ✅ NANDA Index: Added as a Context Agent (screenshot included)
• ✅ Deliverables: Repo link + working endpoint + host screenshots

What worked

• Streamable HTTP transport with session management is stable once the close-loop gotcha is avoided.
• Smithery makes deployment + auth key distribution straightforward.
• Claude Desktop connects cleanly via @smithery/cli run ….

AI Acknowledgement

Parts of this project (tool scaffolding, error fixes, and documentation polish) were produced with AI assistance. The final code, deployment, and testing steps were implemented and verified by me.