Todo MCP Server
A minimal todo app MCP server for ChatGPT that exposes tools for managing tasks and provides an interactive HTML widget interface. It demonstrates how to build MCP servers with React-based UIs and includes development OAuth for ChatGPT connector setup.
README
ChatGPT Todo MCP demo (Apps SDK + React)
A minimal todo app for ChatGPT: an MCP server exposes tools and an interactive HTML UI, built with React + Vite and embedded as a single-file bundle. Includes a small dev OAuth layer so ChatGPT’s connector wizard can complete discovery.
Official reference: Apps SDK Quickstart.
Quick start
npm install
npm start # builds widget (prestart) then runs server on port 8787 by default
-
MCP endpoint:
http://localhost:8787/mcp -
For ChatGPT: expose with HTTPS (e.g. ngrok) and create a connector pointing at
https://<your-host>/mcp. -
If discovery URLs show the wrong scheme/host behind a tunnel, set:
export PUBLIC_BASE_URL=https://your-ngrok-host.example
Project layout
| Path | Role |
|---|---|
server.js |
HTTP router: OAuth discovery + CORS + MCP StreamableHTTPServerTransport on /mcp |
oauth-dev.js |
Dev-only OAuth 2.1 discovery + DCR/PKCE (replace with a real IdP for production) |
widget/ |
Vite + React source for the in-chat UI |
dist/todo-widget.html |
Built single-file HTML (gitignored); loaded by server.js at startup |
Architecture and concepts
One-sentence model
ChatGPT acts as the MCP client. It speaks MCP over HTTPS to your Node server at /mcp. The server registers tools (what the model can call) and a resource (HTML for the widget). The widget runs in an iframe and talks to ChatGPT through a JSON-RPC bridge over postMessage. OAuth metadata on the same origin lets ChatGPT attach the connector; it is separate from MCP tool execution but required for onboarding.
Model Context Protocol (MCP)
MCP is a standard way for a host (ChatGPT) to discover and invoke tools and read resources on a server. This repo uses @modelcontextprotocol/sdk: an McpServer instance registers capabilities and is connected to a transport that maps MCP messages to HTTP (StreamableHTTPServerTransport).
Base MCP vs Apps SDK helpers
@modelcontextprotocol/sdk: coreMcpServer, schemas, transport.@modelcontextprotocol/ext-apps:registerAppToolandregisterAppResourcenormalize UI metadata (which HTML resource to show for a tool) and set the Apps HTML MIME type (RESOURCE_MIME_TYPE).
The widget is registered as a resource at a logical URI (e.g. ui://widget/todo.html). That URI does not need to be a public web URL; the host resolves it via MCP resources/read. Each tool’s _meta.ui.resourceUri points at the same URI so ChatGPT knows which UI surface belongs to which tool.
HTTP front door (server.js)
One Node http.Server handles several surfaces:
- OAuth / discovery (
oauth-dev.js) — well-known URLs and token endpoints ChatGPT expects. - CORS
OPTIONSfor/mcp. - Health
GET /. - MCP
POST/GET/DELETEon/mcpvia the streamable HTTP transport. - 404 for unknown paths.
So you have one process, multiple logical HTTP APIs (OAuth HTTP + MCP HTTP).
Streamable HTTP and server lifetime
The transport is created per incoming MCP request, with sessionIdGenerator: undefined (stateless mode for this demo). A new McpServer is constructed per request and torn down when the response closes.
Important: in-memory todo state (todos in server.js) lives at module scope, not inside the McpServer instance. So state persists for the lifetime of the Node process even though each request gets a new MCP server object.
Tools and the UI contract
Tools (add_todo, complete_todo) declare input schemas (Zod) so the host validates arguments.
Tool results include:
content: usual MCP content (e.g. text) for the model/conversation.structuredContent: JSON consumed by the widget—here{ tasks: [...] }.
Using the same structuredContent shape for every mutation keeps the React UI in sync whether the call was triggered by the user in the widget or by the model in chat.
OAuth (oauth-dev.js)
ChatGPT’s connector flow fetches OAuth protected resource metadata and authorization server metadata (see Apps SDK auth). Without those routes, setup can fail with “Error fetching OAuth configuration.”
This repo ships a development-only authorization server (discovery, dynamic client registration, authorize redirect, PKCE token exchange) scoped to ChatGPT redirect URLs. Do not use it as-is for production—swap in Auth0, Stytch, Cognito, or similar, and verify tokens on MCP requests.
PUBLIC_BASE_URL forces the public https:// origin in metadata when proxies/ngrok do not set Host / X-Forwarded-Proto the way you need.
Widget bridge (widget/src/bridge.ts)
The built HTML runs inside ChatGPT’s iframe. It does not call your /mcp URL like a normal SPA; it uses the MCP Apps UI bridge:
ui/initializethenui/notifications/initialized— handshake with the host.tools/call— ask the host to run a named MCP tool with arguments (same tools the model uses).ui/notifications/tool-result— when the model runs a tool, the host can push the result so the UI updates without a direct return path fromtools/call.
So there are two update paths: RPC responses for UI-initiated calls, and notifications for model-initiated calls.
Why single-file HTML (Vite + vite-plugin-singlefile)
ChatGPT receives the widget as embedded HTML from the MCP resource read, not as “your site + separate JS chunks.” Relative chunk URLs would break in that embedding model. The build produces one dist/todo-widget.html with inlined JS/CSS; server.js reads it at startup into todoHtml.
React is a developer ergonomics layer; the deployable artifact is static HTML.
End-to-end flows
User in ChatGPT: message → model selects a tool → ChatGPT POSTs to your /mcp → tool runs → returns structuredContent.tasks → host shows/updates the widget.
User in the widget: React → tools/call via postMessage → host forwards to MCP → same handlers → RPC result updates state.
Connector setup: ChatGPT hits /.well-known/... on your origin → OAuth linking if required → subsequent MCP calls to /mcp may include Authorization: Bearer ... (enforcing that on every tool is a production step).
Natural next steps
| Area | Direction |
|---|---|
| State | Persist todos in a database; scope by authenticated user id from the access token. |
| Auth | Replace oauth-dev.js with a real IdP; validate issuer, audience, scopes on each MCP request. |
| MCP session | Stateful sessions if you need different streaming or lifecycle semantics. |
| Tools | Richer descriptions/schemas, optional outputSchema, clearer names for model routing. |
| Widget | Same bridge; improve UX, errors, and loading states. |
Scripts
| Script | Description |
|---|---|
npm run build |
Build dist/todo-widget.html from widget/ |
npm start |
npm run build then node server.js |
npm run build:widget |
Vite build only |
Default port: 8787 (PORT env overrides).
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.