Todo MCP Demo

A demo project showing how an AI Agent (MCP Host) uses the Model Context Protocol (MCP) to communicate with Tools, Resources, and Prompts exposed by an MCP Server, over both stdio and HTTP transports.

Live public MCP endpoint: https://todo-mcp-demo.onrender.com/mcp (Streamable HTTP — no API key required; connect with MCP Inspector by choosing the "Streamable HTTP" transport. First request after idle may take ~30-60s to wake up the free Render instance.)

Full specification: docs/00_GLOBAL_RULES.md, docs/01_REQUIREMENTS.md, docs/02_ARCHITECTURE.md, docs/03_IMPLEMENTATION_PLAN.md.

Overview

User → Agent (MCP Host) → MCP Tool → Todo Store → Result → Agent → User

• Todo Store (src/server/todoStore.ts) — in-memory business logic: addTask, listTasks, completeTask. No database, no transport dependency.

• MCP Server (src/server/server.ts) — exposes the Todo Store as:

  • 3 Tools: add_task, list_tasks, complete_task

  • 1 Resource: todo://list

  • 1 Prompt: plan_my_day

• Transports (src/transports/) — stdio.ts and http.ts both boot the same MCP Server Core; no business logic is duplicated between them.

• Agent / MCP Host (src/agent/) — connects to an MCP Server (stdio or HTTP), discovers Tools dynamically, and dispatches Tool calls.

• Skill (src/skills/plan-my-day/SKILL.md) — a reusable workflow: read the todo list via the list_tasks Tool, filter unfinished tasks, and generate a prioritized plan for the day.

Related MCP server: task-manager-mcp

Architecture

                         User
                           │
                           ▼
                    ┌──────────────┐
                    │    Agent     │
                    │  (MCP Host)  │
                    └──────┬───────┘
                           │
                  MCP Client Layer
                           │
        ┌──────────────────┴──────────────────┐
        │                                     │
        ▼                                     ▼
  stdio Transport                      HTTP Transport
        │                                     │
        └──────────────────┬──────────────────┘
                           ▼
                  MCP Server Core
                           │
      ┌──────────────┬──────────────┬──────────────┐
      ▼              ▼              ▼
    Tools        Resources       Prompts
      │
      ▼
   Todo Store

Prerequisites

• Node.js >= 22.9

• npm

Installation

npm install
npm run build

Configuration (optional)

No environment variable is required — every value has a working default. To override one locally, copy the example file:

cp .env.example .env

All npm scripts load .env automatically via Node's built-in --env-file-if-exists flag (no dotenv dependency needed). .env is git-ignored; only .env.example is committed. On hosting platforms (Render/Railway) PORT is injected by the platform itself, so .env is not used in production.

Available npm Scripts

Run the stdio Server

npm run server:stdio

This starts the MCP Server on stdio. Connect with the MCP Inspector:

npx @modelcontextprotocol/inspector node dist/transports/stdio.js

Run the HTTP Server

npm run server:http

Starts an HTTP MCP endpoint at http://localhost:3000/mcp (override the port with the PORT environment variable). Connect with MCP Inspector by choosing the "Streamable HTTP" transport and pointing it at that URL.

Run the Agent

The Agent connects to a running MCP Server, discovers its Tools, and dispatches a single natural-language command.

Against the stdio server (default — the Agent spawns the server itself, no need to start it separately):

npm run agent -- "add task Buy milk"
npm run agent -- "list tasks"
npm run agent -- "complete task <task-id>"

Against a running HTTP server (start it first with npm run server:http in another terminal):

MCP_TRANSPORT=http npm run agent -- "add task Buy milk"
MCP_TRANSPORT=http MCP_HTTP_URL=http://localhost:3000/mcp npm run agent -- "list tasks"

Run the Skill: plan-my-day

See src/skills/plan-my-day/SKILL.md for the full workflow definition. The Agent recognizes the trigger phrase and runs the workflow using the existing list_tasks Tool (no direct access to the Todo Store):

npm run agent -- "plan my day"
# or, against the HTTP server:
MCP_TRANSPORT=http npm run agent -- "plan my day"

Example output:

Today's plan:
1. Buy milk
2. Write report

Demo Walkthrough

npm run agent -- "add task Buy milk"
npm run agent -- "add task Write report"
npm run agent -- "plan my day"

Note: each npm run agent call against the stdio transport spawns a fresh server process, so tasks only persist for the lifetime of a single command. To see tasks persist across multiple Agent calls, start the HTTP server once (npm run server:http) and pass MCP_TRANSPORT=http to every Agent call, as shown above.

Deployment

The HTTP MCP Server (src/transports/http.ts) is deployment-ready:

• It reads the port from the PORT environment variable.

• npm start runs the compiled server directly (node dist/transports/http.js).

Deployed on Render (Free instance type):

• Repository: https://github.com/thienbanho/todo-mcp-demo

• Build command: npm install && npm run build

• Start command: npm start

• No environment variables required — Render sets PORT automatically.

• Live endpoint: https://todo-mcp-demo.onrender.com/mcp

To deploy on Railway instead, the steps are equivalent: connect the repository, set the same build/start commands, and Railway will assign a public URL and PORT automatically.

Verified with a raw MCP initialize + tools/list handshake against the live endpoint (see mcp-session-id flow in src/transports/http.ts); you can also verify interactively with MCP Inspector, using the public /mcp URL as a Streamable HTTP endpoint.

Out of Scope

Per the project spec: no database, authentication, authorization, user management, frontend, Docker, CI/CD, or multi-user support. All Todo data is in-memory and is lost on server restart — this is intentional for a demo project.