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MCP server for Sieve AI startup due diligence — screen startups with the IMPACT-X framework

Project description

PyPI version Python 3.10+ License: MIT MCP Compatible

Sieve MCP Server

AI-powered startup due diligence, delivered as an MCP server. Sieve scores startups across 7 IMPACT-X dimensions (Innovators, Market, Product, Advantage, Commerce, Traction, X-Factor) and recommends whether to take a meeting, pass, or request more information.

Quick Start

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "sieve": {
      "command": "uvx",
      "args": ["sieve-mcp"],
      "env": {
        "SIEVE_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Code

claude mcp add sieve -- uvx sieve-mcp

Then set your API key in the environment:

export SIEVE_API_KEY="your-api-key"

Cursor / Windsurf

Add to your MCP settings:

{
  "mcpServers": {
    "sieve": {
      "command": "uvx",
      "args": ["sieve-mcp"],
      "env": {
        "SIEVE_API_KEY": "your-api-key"
      }
    }
  }
}

Environment Variables

Variable Required Default Description
SIEVE_API_KEY Yes Your Sieve API key. Get one at sieve.arceusxventures.com/settings
SIEVE_API_URL No https://api.sieve.arceusxventures.com API base URL (override for self-hosted)

Available Tools

Tool Description Read-only
sieve_screen Run a Quick Screen on a startup No
sieve_status Check analysis progress Yes
sieve_summary Get full results of a completed analysis Yes
sieve_usage Check API usage for current billing period Yes

Example Usage

A typical workflow in any MCP-compatible AI assistant:

  1. Screen a startup:

    "Run a Sieve screen on Acme Corp at acme.com"

  2. Poll for progress (analysis takes 2-5 minutes):

    "Check the status of that Sieve analysis"

  3. Get results:

    "Show me the Sieve summary for that analysis"

  4. Check usage:

    "How many Sieve screens do I have left this month?"

Running with Docker

docker build -t sieve-mcp .
docker run -p 8080:8080 -e SIEVE_API_KEY=your-key sieve-mcp

Development

# Install locally
pip install -e .

# Run in stdio mode (for MCP clients)
sieve-mcp

# Run in HTTP mode (for remote/container deployment)
sieve-mcp http

License

MIT

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