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MCP Agent Homework

A TypeScript MCP (Model Context Protocol) system built for the assignment in MCP_HOMEWORK_SKILL.md: an Agent Host that loads an Agent Skill (SKILL.md), connects to three MCP servers over all three required transports, discovers/aggregates their tools, and lets Gemini select and call the right tool on the right server.

Architecture

                          Agent Host (src/host)
                     skill-loader + connection-manager
                       + tool-bridge + gemini-client
                                 |
              +------------------+------------------+
              |                  |                   |
              v                  v                   v
        stdio server       local HTTP server    public HTTP server
     (src/servers/stdio-  (src/servers/http-   (same http-server.ts,
        server.ts)          server.ts, no auth)   API-key protected)
              |                  |                   |
              +------------------+-------------------+
                                 |
              shared tool logic (src/servers/shared/tools.ts)
       3 tools (calculator, text_stats, unit_convert) + 1 resource + 1 prompt
  • src/servers/shared/tools.ts — the single implementation of the 3 tools, 1 resource, and 1 prompt, registered identically on every server so the same logic is reused everywhere (no duplicated business logic).

  • src/servers/stdio-server.ts — MCP over stdio (spawned as a child process).

  • src/servers/http-server.ts — MCP over Streamable HTTP. The exact same file/code runs both the "local" and "public" servers; the only difference is configuration (PORT, PUBLIC_MCP_API_KEY).

  • src/host/connection-manager.ts — the MCP Host: connects to every configured server, discovers tools/resources/prompts, namespaces tool names as <namespace>__<tool> to avoid collisions, and dispatches tool calls back to the owning server.

  • src/host/tool-bridge.ts — converts discovered MCP tools into Gemini function declarations.

  • src/host/gemini-client.ts — the Gemini tool-calling loop (send message → read function calls → dispatch via connection manager → send function responses back → repeat until final text).

  • src/host/skill-loader.ts — loads SKILL.md and injects it as the model's system instruction, so the skill actively shapes tool usage.

  • src/host/agent-host.ts — wires the above together from config/servers.json.

  • src/host/cli.ts — CLI entry point (interactive or --demo).

Related MCP server: mcp-tools-server

Setup

npm install

Secrets live in api.env (already gitignored):

API_KEY=your-gemini-api-key
# Optional, only needed once you deploy the public server:
# PUBLIC_MCP_URL=https://your-app.onrender.com/mcp
# PUBLIC_MCP_API_KEY=some-strong-random-key

Running each component

stdio server (20 pts)

npm run server:stdio            # run directly
npm run inspector:stdio         # open MCP Inspector against it

Inspector will discover 3 tools (calculator, text_stats, unit_convert), 1 resource (docs://unit-conversions), and 1 prompt (explain-tool-result), and can execute/read all of them.

Local HTTP server

npm run server:http             # listens on http://127.0.0.1:8787/mcp, no auth
npm run inspector:http          # then connect Inspector to that URL

Public HTTP server (15 pts)

The same http-server.ts becomes the "public" server once PUBLIC_MCP_API_KEY is set — every request then requires a matching x-api-key header; missing/invalid keys get 401 Unauthorized.

$env:PORT=8788; $env:PUBLIC_MCP_API_KEY="a-strong-secret"; npm run server:http

Deploying it publicly (Render.com, using the included render.yaml):

  1. git init && git add -A && git commit -m "MCP homework" then push to a GitHub repo you own.

  2. In Render: New +Blueprint → select the repo (it reads render.yaml automatically), or create a Web Service manually with:

    • Build command: npm install && npm run build

    • Start command: npm run start:http

    • Health check path: /health

  3. In the Render dashboard, set the PUBLIC_MCP_API_KEY environment variable to a strong secret (never commit it).

  4. Once deployed, put the resulting URL + key into api.env: PUBLIC_MCP_URL=https://<your-service>.onrender.com/mcp and PUBLIC_MCP_API_KEY=<same secret>.

  5. Validate with Inspector:

    • No key → rejected: curl -X POST https://<url>/mcp -H "Content-Type: application/json" -d "{...}" returns 401.

    • With key → works: pass --header "x-api-key: <secret>" to npx @modelcontextprotocol/inspector --cli <url> --method tools/list.

Agent Host

npm run agent          # interactive CLI
npm run agent:demo      # runs a scripted set of demo queries

On startup the host:

  1. Loads SKILL.md as the system instruction.

  2. Reads config/servers.json and connects to the stdio server (spawned automatically), the local HTTP server (must already be running), and the public HTTP server (skipped automatically if PUBLIC_MCP_URL/PUBLIC_MCP_API_KEY aren't set — it's optional so the demo still works without a live deployment).

  3. Discovers and namespaces every tool, hands them to Gemini, and dispatches each tool call Gemini makes to the correct MCP server.

Configuration

Server registration is data-driven via config/servers.json — add/remove servers there instead of editing host code. ${VAR} in a url is resolved from process.env at connect time; apiKeyEnv names the env var whose value is sent as x-api-key.

Agent Skill

SKILL.md instructs the agent to prefer calling tools over guessing at arithmetic/conversions/text stats, to pick one namespaced tool per logical request, to consult the docs://unit-conversions resource when unsure about supported conversions, and to explain results in plain language. It is loaded verbatim into the Gemini system instruction on every run (see src/host/skill-loader.ts), so its rules directly affect tool selection and response style — observable in the demo output (e.g. the agent always calls a tool for arithmetic instead of computing it itself).

Security notes

  • No secrets are committed; api.env is gitignored and the public server only reads PUBLIC_MCP_API_KEY from the environment.

  • The public HTTP server rejects any request without a matching x-api-key header (401), and accepts requests once a valid key is supplied.

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