IdeaLift MCP Server

Decision intelligence for AI assistants via Model Context Protocol.

Connect Claude, ChatGPT, and other AI assistants to your product backlog. Capture feedback, track decisions, and manage ideas without leaving your AI workflow.

What it does

• Normalize ideas — Transform raw text into structured feature requests, bug reports, or tasks
• Signal aggregation — Capture product feedback from Slack, Teams, Discord, and GitHub
• Decision tracking — Record who decided what, when, and why with full audit trails
• RICE scoring — Prioritize ideas with Reach, Impact, Confidence, and Effort scores
• Ticket creation — Push structured ideas to GitHub Issues, Jira, or Linear

MCP Tools

Plus proxy tools for full IdeaLift API access (ideas, signals, decisions, roadmap).

Setup

1. Install dependencies

npm install

2. Configure environment

cp .env.example .env

Required environment variables:

3. Build and run

npm run build
npm start

Or for development:

npm run dev

The MCP server starts on port 3001 (configurable via PORT).

4. Connect to your AI assistant

SSE endpoint: http://localhost:3001/mcp

Add this URL as an MCP server in Claude Desktop, ChatGPT, or any MCP-compatible client.

Transport

Uses Server-Sent Events (SSE) transport with automatic keep-alive pings every 15 seconds.

OAuth

Built-in OAuth 2.0 flow for connecting AI assistant users to their IdeaLift accounts. Supports authorization code grant with PKCE.

Deployment

Deployed as an Azure App Service. See the IdeaLift docs for hosted access.

License

MIT