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 as claude.ai artifacts it builds itself — from raw run_sql
data, or from run_valuation's payload plus a frozen deal-sheet template.
Maps are the one surface the server still renders: it hands the renderer a
spec it validates, hydrates, and serves once.
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, map handle store, identity, logging |
| Pytest suite covering the tools, engine, maps, and guards |
See CLAUDE.md for the full architecture reference.
Related MCP server: nl2sql-mcp
The tools
run_sql— guarded, SELECT-only, capped exploration queryforecast_wells/run_valuation— well-decline forecasting and economics, returning the data behind a claude.ai deal-sheet artifactmap— a MapLibre GL well/unit/PLSS mapget_skill— fetches a packaged, occasional-use procedure (e.g. dataroom extraction)save_dataroom_extraction— persists a dataroom extraction so the deal record outlives the chatmessage_team— files bugs, feedback, and data requests to the team (durable row + best-effort email)
Requirements
Python 3.11+ and a virtualenv (
.venv)Node 20+ (for the renderer build)
A Postgres database whose schema matches
utils/schemas.pyandprompts/outer/shared_schema.md. Populating that database (primary-source ingestion) is out of scope for this repo — pointCC_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 CC_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.
Maintenance & contributions
This is a working platform maintained by one person alongside a full-time job. It's open-sourced for transparency and as a reference for building real systems on MCP + skills. Issues and PRs are welcome, but responses are best-effort — please set expectations accordingly.
License
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Maintenance
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