Startup Ecosystem Intelligence MCP Server

VC deal sourcing and startup due diligence intelligence using alternative data signals from patents, GitHub, job postings, and corporate registries. This MCP server orchestrates 8 data sources to produce Innovation Velocity Scores (0-100), decode hiring signal patterns, analyze competitive moats, verify corporate structures, and generate comprehensive deal memos. No reliance on self-reported fundraising data -- all signals come from observable public behavior.

What data can you access?

Data Point	Source
Corporate registration, officers, and entity status	OpenCorporates
US patent filings, assignees, and claims	USPTO Patent Search
European patent filings and applications	EPO Patent Search
Open source repositories, stars, forks, contributors	GitHub Repo Search
Website technology stack detection	Tech Stack Detector
Job postings, seniority mix, role distribution	Job Market Intelligence
Pre-publication research activity	ArXiv Preprint Search
SaaS market positioning and feature comparison	SaaS Competitive Intelligence

MCP Tools

Tool	Price	Description
discover_startups	$2.00	Discover startups in a sector via corporate registries, GitHub, and SaaS competitive intelligence
assess_innovation_velocity	$2.00	Score innovation velocity from patent filings (USPTO + EPO), GitHub activity, and ArXiv publications
decode_hiring_signals	$2.00	Decode hiring patterns -- role mix reveals strategy direction (Building/Scaling/Pivoting/Maintaining)
analyze_competitive_moat	$2.00	Analyze competitive moat via tech stack, patent portfolio, competitor density, and community
verify_corporate_structure	$2.00	Verify corporate registration, entity status, jurisdictions, and officer data via OpenCorporates
track_technology_trends	$2.00	Track emerging technology trends from ArXiv research, GitHub projects, and patent filings
benchmark_against_cohort	$2.00	Benchmark a startup against its competitive cohort on tech stack, hiring, and market positioning
generate_deal_memo	$5.00	Comprehensive deal memo with all 8 sources, 4 scoring models, and investment thesis

Data Sources

• OpenCorporates -- Corporate registration verification across 140+ jurisdictions with officers, filings, and entity status
• USPTO Patent Search -- US patent portfolio analysis including filing velocity, claim breadth, and assignee data
• EPO Patent Search -- European patent filings for global IP coverage assessment
• GitHub Repo Search -- Open source activity as engineering culture proxy: stars, forks, contributor count, commit velocity
• Tech Stack Detector -- Website technology identification revealing infrastructure choices and modernity
• Job Market Intelligence -- Job posting analytics for hiring pattern analysis and strategic direction inference
• ArXiv Preprint Search -- Pre-publication research activity indicating R&D investment and academic connections
• SaaS Competitive Intelligence -- Market positioning, feature comparison, and competitive density analysis

How the scoring works

The MCP produces four scoring dimensions that combine into a deal rating:

Innovation Velocity Score (0-100) quantifies innovation output normalized by company age and size. Combines patent filing rate (USPTO + EPO), GitHub activity (repos, stars, commit frequency), and ArXiv publication velocity. High scores indicate rapid IP creation and R&D investment.

Hiring Signal Decoder analyzes job posting role mix to infer strategic direction. Heavy ML/AI hiring signals an AI pivot. Predominant sales hiring indicates growth stage. Executive search suggests strategic transition. The system classifies companies as Building, Scaling, Pivoting, or Maintaining based on role distribution patterns.

Competitive Moat Analyzer scores defensibility from IP breadth (patent portfolio across technologies), technology uniqueness (tech stack complexity and modernity), GitHub community strength (contributor diversity), and competitive density (number and proximity of SaaS competitors).

Corporate Registration Health Check verifies entity status, flags inactive or dissolved entities, identifies unusual jurisdiction choices, and detects rapid officer changes that may indicate governance issues.

Deal Rating	Interpretation
Strong Buy	High innovation velocity, strong moat, healthy corporate structure
Diligence	Promising signals, proceed to detailed due diligence
Watch	Mixed signals, monitor for development
Pass	Low innovation velocity, weak moat, or corporate red flags

How to connect this MCP server

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "startup-ecosystem": {
      "url": "https://startup-ecosystem-intelligence-mcp.apify.actor/mcp"
    }
  }
}

Programmatic (HTTP)

curl -X POST https://startup-ecosystem-intelligence-mcp.apify.actor/mcp \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"assess_innovation_velocity","arguments":{"company":"Anthropic"}},"id":1}'

This MCP also works with Cursor, Windsurf, Cline, and any other MCP-compatible client.

Use cases for startup ecosystem intelligence

VC Deal Sourcing with Alternative Data

Discover startups through patent filings, GitHub activity, and ArXiv publications rather than relying on pitch decks. Quantify innovation velocity to filter the pipeline before taking meetings.

Corporate Venture Acquisition Scouting

Identify potential acquisition targets by technology domain. Map competitive moats and IP portfolios to assess strategic value and defensibility before approaching founders.

Accelerator Portfolio Benchmarking

Benchmark portfolio company performance against comparable cohorts on hiring patterns, GitHub activity, patent output, and competitive positioning to identify which companies need support.

Technology Trend Scouting

Track emerging technology trends from research (ArXiv) through development (GitHub) to commercialization (patents and hiring). Identify investment themes at the research stage before markets form.

Startup Due Diligence Automation

Verify corporate structure, assess IP strength, and decode hiring strategy in a single deal memo. Replace weeks of manual research with structured, data-driven intelligence.

Competitive Landscape Mapping

Map the competitive density around a technology or market. Identify white space opportunities and assess whether a startup's positioning provides defensible differentiation.

How much does it cost?

This MCP uses pay-per-event pricing. You are only charged when a tool is called.

The Apify Free plan includes $5 of monthly platform credits, which covers 2 deal memos or several individual tool calls.

Example Use	Approximate Cost
Innovation velocity assessment	$2.00
Competitive moat analysis	$2.00
Full deal memo (all 8 sources)	$5.00
Screen 10 startups with deal memos	~$50.00

How it works

1. You provide a company name (and optionally a website URL) via any MCP client
2. The MCP runs up to 8 Apify actors in parallel querying OpenCorporates, USPTO, EPO, GitHub, Tech Stack Detector, Job Market Intelligence, ArXiv, and SaaS Competitive Intelligence
3. Scoring algorithms process the combined data -- Innovation Velocity, Hiring Signals, Competitive Moat, and Corporate Health are computed
4. Structured JSON is returned with the deal rating, scores, investment thesis, red flags, and supporting data

FAQ

Q: Does this access Crunchbase or PitchBook data? A: No. This uses public sources (patents, GitHub, ArXiv, job postings, corporate registries) to generate alternative signals that do not rely on self-reported fundraising data.

Q: How does it compare to traditional deal sourcing? A: Traditional deal sourcing relies on network referrals and self-reported data. This MCP provides quantified signals from observable behavior (patent filings, GitHub commits, hiring patterns) that complement but do not replace relationship-driven sourcing.

Q: Can it assess pre-revenue startups? A: Yes. Patent filings, ArXiv publications, GitHub activity, and hiring patterns provide signals even for companies with no revenue. The Innovation Velocity Score is normalized by company age.

Q: Is the data real-time? A: Data is fetched live at query time from each source. Patent and corporate registry data may lag by days to weeks depending on the registry.

Q: Is it legal to use this? A: All data sources are publicly available. See Apify's guide on web scraping legality.

Q: Can I combine this with other MCPs? A: Yes. Use alongside the M&A Target Intelligence MCP for acquisition screening or the Workforce Competitive Intelligence MCP for talent movement analysis.

Related MCP servers

MCP Server	Description
ryanclinton/m-and-a-target-intelligence-mcp	Pre-acquisition target screening
ryanclinton/academic-commercialization-pipeline-mcp	Research-to-product technology scouting
ryanclinton/workforce-competitive-intelligence-mcp	Talent movement and organizational risk
ryanclinton/tech-ecosystem-analysis-mcp	Technology ecosystem mapping and risk scoring

Integrations

This MCP server is built on the Apify platform and supports:

• Apify API for programmatic deal sourcing pipeline integration
• Scheduled runs via Apify Scheduler for recurring portfolio monitoring
• Webhooks for triggering alerts when innovation velocity scores change significantly
• Integration with 200+ Apify actors for extending data coverage