Crude Code MCP Server
OfficialProvides a map tool that renders MapLibre GL maps of wells, units, and PLSS data.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Crude Code MCP Servershow me a map of wells in the Permian basin"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Crude Code — MCP Server & Renderer
An oil & gas data-analytics platform built as a Model Context Protocol server plus an inline renderer that draws results directly inside the host chat app (Claude Desktop / claude.ai).
The design principle: the model does the thinking; the server does the deterministic work. There are no inner agents. The host model explores a Postgres database with a guarded, read-only SQL tool, then publishes finished deliverables — data briefings, well valuations, and maps — by handing the server a spec it validates, hydrates, and renders.
What's in here
Path | What it is |
| FastMCP server ( |
| Inline React + TypeScript app (Vite, Tailwind) built to a single |
| Model-facing prompts and the shared DB-schema reference |
| SQL guard, spec validation/hydration, handle stores, identity, logging |
| Pytest suite covering the tools, engine, maps, and guards |
See CLAUDE.md for the full architecture reference.
Related MCP server: NLSQL MCP Server
The tools
run_sql— guarded, SELECT-only, capped exploration queryrun_data_analysis— validates + hydrates a model-authored briefing spec and renders it inlineforecast_wells/run_valuation— well-decline forecasting and economics, producing an interactive deal sheetexport_valuation_xlsx— a live, editable Excel model of a valuation runmap— a MapLibre GL well/unit/PLSS map
Requirements
Python 3.11+ and a virtualenv (
.venv)Node 20+ (for the renderer build)
A Postgres database whose schema matches
utils/schemas.pyandprompts/inner/shared_schema.md. Populating that database (primary-source ingestion) is out of scope for this repo — pointEI_DB_URLat your own.
Quick start
# 1. Python deps
python -m venv .venv
.venv/bin/pip install -r requirements.txt
# 2. Configure environment
cp .env.example .env # then fill in EI_DB_URL and SUPABASE_DATABASE_URL
# 3. Run the MCP server (port 9000, /mcp endpoint)
.venv/bin/python server/mcp_server.py
# 4. Build the renderer
cd renderer && npm install && npm run build # -> dist/app.htmlTesting
.venv/bin/pytest -qTests that need a database, the Anthropic API, or network access auto-skip when the corresponding environment variable is unset.
For frontend iteration without the host app:
cd renderer && npm run dev # http://localhost:5173/preview.htmlThis renders the real components against committed fixtures with hot reload.
License
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