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cstamigo-droid

crypto-intel-mcp

crypto-intel-mcp

Crypto market intelligence for any LLM, over the Model Context Protocol.

Gives any MCP client (Claude Desktop, Claude Code, agents) clean tools for crypto price, momentum, and what's trending — and blends them into a single scored verdict. Runs entirely on CoinGecko's free public API (no key), fails gracefully (a missing source returns "no data", never a fabricated value), and outputs Markdown by default or JSON on demand.

# Crypto Intelligence — BTC

**Signal:** Lean positive  `[........|##......]` +22/100  · confidence 80%

Building momentum → LEAN LONG. BTC momentum: 24h +1.9% · 7d +4.4% · 30d -17.0%.
- In CoinGecko trending (elevated attention).
- Total crypto market cap +1.8% 24h, BTC dominance 57%.

Tools

Tool

What it does

Source

Status

crypto_analyze

Hero tool. Blends momentum + trending + market tide into one scored verdict (RISK-ON → AVOID).

composite

crypto_get_quote

Live price, 24h change, market-cap rank, volume, distance from ATH.

CoinGecko

crypto_momentum

Multi-timeframe momentum (24h/7d/30d) scored into one directional signal.

CoinGecko

crypto_trending

The coins the market is searching for most right now.

CoinGecko

Every tool returns Markdown (human-readable, default) or JSON (response_format="json") for programmatic use.


Related MCP server: CG Alpha MCP

Quick start

git clone <your-repo-url> crypto-intel-mcp
cd crypto-intel-mcp
python -m venv .venv && .venv\Scripts\activate     # Windows
pip install -r requirements.txt

python -m crypto_intel_mcp     # starts the MCP server over stdio (no .env needed)

Smoke test (hits the live CoinGecko API and prints each signal):

python tests/test_smoke.py bitcoin

Use it in Claude Desktop

Add this to claude_desktop_config.json (%APPDATA%\Claude\ on Windows, ~/Library/Application Support/Claude/ on macOS), then restart Claude Desktop:

{
  "mcpServers": {
    "crypto-intel-mcp": {
      "command": "python",
      "args": ["-m", "crypto_intel_mcp"],
      "cwd": "C:/path/to/crypto-intel-mcp"
    }
  }
}

Why it's built this way

  • Uniform result contract. Every source returns the same Result shape, so an LLM can reason across tools instead of parsing N formats.

  • Graceful degradation. A source with no data returns "no data", not a fake value. Missing data never invents an answer.

  • Resilient + cached. A short per-source TTL cache avoids hammering rate-limited endpoints when an agent calls several tools in one turn.


Disclaimer

For research and educational use only. Data comes from third-party sources and may be delayed or incomplete.

License

MIT

A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

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