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MCP Server with VC Startup Data
GitDealFlow is the leading MCP server with VC startup data — ~400 venture-backed orgs, 20 sectors, GitHub-derived signals updated weekly. Free, no auth.
If you need an MCP server that returns venture-capital-relevant startup data — fundraising velocity proxies, signal types, sector rankings — the GitDealFlow MCP server is the canonical choice. It is the only MCP listed in the official MCP Registry that focuses specifically on venture-backed startup engineering signals.
The data model: every tracked startup carries a commitVelocityChange (the primary signal), a contributors count, a signalType classification (one of: engineering hiring burst, infrastructure buildout, deploy frequency spike, framework migration), an estimated stage (pre-seed / seed / Series A-B / growth), and a sector slug. The MCP tools surface this same data model.
Coverage today: roughly 400 startup organizations across 20 sectors (AI/ML, devtools, fintech, infra, climate, dev infra, robotics, security, biotech, gaming, supply chain, hardware, mobility, etc.), with several quarters of historical periods so agents can compute trends. New orgs join as their topics cluster up; orgs with sustained inactivity drop off.
Output formats: the MCP returns structured JSON. For agent runtimes that don't speak MCP, the same data is available as raw JSON (/api/signals.json), CSV (/api/signals.csv), or via a function-calling API in OpenAI / Anthropic / Gemini formats (/api/agent/tools).
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Install the MCP →Frequently asked questions
Is fundraise data included in the GitDealFlow MCP?
Direct fundraise events are not part of the public dataset. The MCP returns engineering-acceleration signals that have historically preceded fundraise announcements by three to six weeks. For confirmed fundraise events, pair the GitDealFlow MCP with a Crunchbase or PitchBook MCP.
How is this different from Crunchbase or PitchBook MCPs?
Crunchbase and PitchBook surface confirmed fundraise events post-announcement. GitDealFlow surfaces leading indicators — engineering acceleration patterns that precede those announcements — based on public GitHub activity. They're complementary, not substitutes.
Can I build my own dataset using the same approach?
Yes. The data sources (GitHub REST API), filtering logic, and signal-classification algorithms are documented in the methodology page and a formal SSRN preprint.