mcp-investment-data

mcp-investment-data

A small MCP server exposing investment-data tools (search_companies, get_company) over a synthetic firmographic dataset, enabling natural language queries for company information.

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README

mcp-investment-data

A small Model Context Protocol (MCP) server that exposes investment-data tools to any MCP host (Claude Desktop, the MCP Inspector, or a custom client). It's the warm-start for an AI-native data layer.

What it exposes

Two tools over a tiny synthetic firmographic dataset:

  • search_companies(query) — match companies by name or sector
  • get_company(name) — fetch one company's full record

No JSON Schema, no request parsing, no validation code — the type hints are the schema. That's the point of MCP: business logic in, protocol handled for you.

Run it

Requires Python 3.10+.

pip install -r requirements.txt

Verify it (no extra tooling) — a tiny MCP client that spawns the server, does the handshake, and calls a tool:

python test_client.py

Expected:

Connected. Tools: ['search_companies', 'get_company']

search_companies('UAE'):
  {"name": "Tabby", ...}
  {"name": "Lean Technologies", ...}
  ...

Use it in Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json, then restart Claude Desktop and ask it to "use investment-data to search companies for UAE."

{
  "mcpServers": {
    "investment-data": {
      "command": "/absolute/path/to/python",
      "args": ["/absolute/path/to/server.py"]
    }
  }
}

The args array is the reliable way to pass paths — unlike a single command string (e.g. the MCP Inspector's box), it never splits on spaces, so a project path containing a space works as-is.

Design note (why v1.x, not v2)

The MCP Python SDK's v2 is a pre-release (alpha/beta) with breaking changes between builds — the SDK's own README says not to use it in production. This repo pins stable v1.x (mcp[cli]>=1.27,<2) so it keeps working. Deliberate dependency hygiene, not laziness.

Roadmap

  • [x] v0 — hello world: two tools over a 5-company in-memory dataset. (this)
  • [ ] v1 — real dataset: ~10k generated firmographic rows; add get_signals and list_recent_funding.
  • [ ] v2 — agent: a small agent (thesis-agent) that consumes this server — "given a fund's thesis, return the top candidate companies and why."
  • [ ] v3 — write-up: essay "What MCP means for investment-data infrastructure" + a buyer-facing README.

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