The dashboard nobody visited
I built a startup signal dashboard. It tracked GitHub engineering acceleration across 2,000+ startup organizations and ranked them by commit velocity, contributor growth, and repo expansion. The data was solid. The UI was clean.
Nobody came back to it.
Investors signed up, bookmarked the URL, and forgot about it. Because that's not how knowledge workers operate in 2026. They don't open dashboards. They ask their AI assistant.
The shift
I had a realization: the best distribution channel for a data product isn't a website. It's being embedded in the tool people already use 8 hours a day.
For investors using Claude, that means an MCP server.
What I built
VC Deal Flow Signal monitors GitHub engineering activity across startup organizations and surfaces the ones showing unusual acceleration. The hypothesis: engineering acceleration (measured as the rate of change in commit velocity) is a leading indicator for fundraise announcements, usually by 6 to 12 weeks.
The MCP server exposes 5 tools:
Tool What it does
get_trending_startups Top 20 startups by engineering acceleration
search_startups_by_sector Startups ranked within a specific sector (20 sectors)
get_startup_signal Signal profile for a specific startup
get_signals_summary Dataset overview, formats, and links
get_methodology How the signals are calculated
All data is fetched live from the public API at signals.gitdealflow.com. No API key required.
How I built the MCP server
The server is TypeScript, uses the official @modelcontextprotocol/sdk, and runs over stdio transport.
The entire implementation is about 250 lines:
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
const server = new Server(
{ name: "vc-deal-flow-signal", version: "1.0.0" },
{ capabilities: { tools: {} } }
);
// Register tools, handle requests, fetch from API
// Full source: github.com/kindrat86/mcp-deal-flow-signal
Each tool fetches live data from signals.gitdealflow.com/api/signals.json and formats it as structured text. The server doesn't bundle any data — it's a thin wrapper around the public API.
Publishing to the MCP ecosystem
Getting the server discoverable took three steps:
- Publish to npm
npm publish --access public
Package: @gitdealflow/mcp-signal
- Publish to the official MCP Registry
brew install mcp-publisher
mcp-publisher login github
mcp-publisher publish
This required a server.json manifest with the registry schema and an mcpName field in package.json that matches the registry namespace.
- Submit to directories
I submitted to 8 directories in total:
Official MCP Registry (published)
npm (published)
awesome-mcp-servers (PR open)
Glama (approved)
mcp.so (submitted)
MCP Market (submitted)
PulseMCP (auto-ingests from registry)
Cline Marketplace (submitted)
The whole process from zero to published took about 3 hours.
Install it
Add to your Claude Desktop or Claude Code config:
{
"mcpServers": {
"vc-deal-flow-signal": {
"command": "npx",
"args": ["-y", "@gitdealflow/mcp-signal"]
}
}
}
Then ask Claude: "Which startups are accelerating in fintech?" or "Show me the signal profile for roboflow."
What I learned
MCP servers are the new API. If your product serves data, an MCP server is the highest-leverage distribution channel you can build. It took 2 hours to build and gets your product embedded in the user's workflow permanently.
The ecosystem is early but growing fast. The official registry exists, directories are active, and every major AI tool supports MCP. Getting in now means less competition for visibility.
The best funnel is invisible. When an investor asks Claude about startup signals and gets my data, they didn't "visit my website" or "open my app." They used my product without knowing they entered a funnel. That's the future of distribution.
Links
Website: gitdealflow.com
npm: @gitdealflow/mcp-signal
GitHub: kindrat86/mcp-deal-flow-signal
Live data: signals.gitdealflow.com
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