lmwharton/sieve-mcp

lmwharton/sieve-mcp

vc analyst for pitch deck to memo gen

Category
Visit Server

README

PyPI version Python 3.10+ License: MIT MCP Compatible

Sieve MCP Server — AI-Powered Venture Capital Due Diligence

The first MCP server purpose-built for venture capital. Drop a company name into Claude, Cursor, or Windsurf and get a quantified investment memo in 5 minutes — not a ChatGPT summary, a real analyst-grade IMPACT-X assessment with every claim verified against evidence.

"Screen a startup called Acme Corp" → Sieve researches the company, scores it across 7 dimensions, verifies every claim, and tells you: Take the meeting or Pass.

Why Sieve?

Most VCs screen 50+ deals a month. Most of those are obvious passes — but you still spend 2-3 hours per deal on basic diligence before you know that. Sieve does that work in 5 minutes.

What You Get

Capability Details
Investment Memo Full analyst-grade memo with executive summary, key strengths, critical concerns, and actionable recommendation — not a ChatGPT summary
Deal Scoring (0-140) Quantified Sieve Score across 7 IMPACT-X dimensions — structured, repeatable, comparable across your portfolio
Red Flag Detection Automatically surfaces deal-breakers: founder risk, market timing issues, unsustainable unit economics, missing traction, competitive threats
Evidence Verification Every finding tagged as Documented, Discovered, Inferred, or Missing — cross-references pitch deck claims against real-world evidence
Competitive Landscape Maps competitors, identifies moat strength, evaluates defensibility and switching costs
Financial Model Assessment Evaluates unit economics, pricing power, revenue model viability, and path to profitability
Market Sizing TAM/SAM/SOM analysis with timing assessment — is the market ready?
Team Evaluation Founder-market fit, team completeness, domain expertise, execution track record
Traction Analysis Growth metrics, customer validation, revenue signals, engagement patterns
Real-time Deal Chat Ask follow-up questions, challenge findings, explore what-if scenarios, dig into any dimension
Sector-Aware Analysis Adapts benchmarks for fintech, healthtech, deeptech, climate, SaaS, consumer, and more
Stage-Calibrated Different expectations for pre-seed vs seed vs Series A — doesn't penalize early-stage for missing late-stage metrics

What Makes Sieve Different

  • Not a wrapper around ChatGPT. Sieve runs a structured multi-agent analysis pipeline with real-time web research, evidence verification, and domain-specific benchmarks.
  • We tell you what we don't know. Every finding is evidence-typed (Documented / Discovered / Inferred / Missing) so you see exactly what's verified and where the gaps are.
  • Repeatable framework. The same IMPACT-X methodology every time, so you can compare deals apples-to-apples across your portfolio.
  • Built by VCs. Not a generic AI tool adapted for investing — purpose-built for the way investors actually evaluate deals.

IMPACT-X Framework

Dimension What Sieve evaluates
I — Innovators Founding team quality, experience, domain expertise
M — Market Opportunity size, timing, tailwinds
P — Product Solution strength, differentiation, technical depth
A — Advantage Competitive moat, defensibility, switching costs
C — Commerce Business model, unit economics, pricing power
T — Traction Growth metrics, validation signals, customer evidence
X — X-Factor Unique qualities, timing advantages, intangibles

Each dimension scores 0-20. Total Sieve Score ranges from 0-140.

Quick Start

Install

pip install sieve-mcp

Or run directly without installing:

uvx sieve-mcp

Get Your API Key

  1. Sign up free at app.sieve.arceusxventures.com
  2. Go to Settings → copy your API key
  3. Free tier: 2 screens/month. Pro: unlimited.

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
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"
      }
    }
  }
}

Available Tools

Tool What it does Read-only
sieve_screen Start a Quick Screen — pass a company name, optional website URL, pitch deck text, or description No
sieve_status Poll analysis progress — see which dimensions are complete and current scores Yes
sieve_summary Get the full investment memo — Sieve Score, recommendation, strengths, concerns, evidence Yes
sieve_usage Check how many screens you've used this billing period Yes

Example Workflow

Just talk to your AI assistant naturally:

1. Screen a startup

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

2. Check progress (analysis takes 2-5 minutes)

"What's the status of that Sieve analysis?"

3. Get the full investment memo

"Show me the Sieve results for Acme Corp"

4. Explore the deal

"What are the red flags? Anything that should kill this deal?"

"How strong is their competitive moat? Who are the main competitors?"

"Walk me through their unit economics — is this business model viable?"

"How does the founding team stack up? Any gaps?"

"What's the market timing like? Is this too early or too late?"

"Compare this deal to the last three I screened"

5. Check your usage

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

Pro tip: Upload a pitch deck for deeper analysis

Paste pitch deck text or founder meeting notes for maximum accuracy:

"Screen Acme Corp — here's their pitch deck text: [paste]. Also check acme.com"

Sieve cross-references every pitch deck claim against real-world evidence. When a founder says "fastest-growing in the category," Sieve checks if that's actually true.

More things you can ask

Use case Example prompt
Quick pass/take meeting "Screen this company and give me the bottom line"
Investment memo for IC "Generate a full investment memo I can present to my partners"
Red flag check "What are the deal-breakers for this startup?"
Competitive analysis "Who competes with this company and how defensible are they?"
Financial viability "Does their business model make sense? What are the unit economics?"
Team assessment "Evaluate the founding team — any gaps or concerns?"
Market validation "Is the market real? What's the TAM and timing?"
Batch screening "Screen these 5 startups and rank them by Sieve Score"
Follow-up prep "Based on this analysis, what questions should I ask the founders?"
Portfolio comparison "How does this deal compare to others I've screened?"

Who Uses Sieve

  • Solo GPs screening 50+ deals/month — stop spending hours on obvious passes
  • Angel investors evaluating startups outside their domain — Sieve brings sector expertise
  • Emerging fund managers building a repeatable diligence process — consistent framework, every time
  • Accelerators standardizing evaluation — compare apples to apples across your cohort

Environment Variables

Variable Required Default Description
SIEVE_API_KEY Yes Your Sieve API key (get one free)
SIEVE_API_URL No https://api.sieve.arceusxventures.com API base URL

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

Also Available As

Sieve isn't just an MCP server. Use it however fits your workflow:

Links

License

MIT


Built by ArceusX Ventures — from VCs, for VCs.

<!-- mcp-name: io.github.lmwharton/sieve-mcp -->

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured