Skip to main content
Glama
crude-code

Crude Code MCP Server

Official
by crude-code

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

server/

FastMCP server (mcp_server.py), the valuation engine (valuation/), and maps (maps/)

renderer/

Inline React + TypeScript app (Vite, Tailwind) built to a single dist/app.html

prompts/

Model-facing prompts and the shared DB-schema reference

utils/

SQL guard, spec validation/hydration, handle stores, identity, logging

tests/

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 query

  • run_data_analysis — validates + hydrates a model-authored briefing spec and renders it inline

  • forecast_wells / run_valuation — well-decline forecasting and economics, producing an interactive deal sheet

  • export_valuation_xlsx — a live, editable Excel model of a valuation run

  • map — 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.py and prompts/inner/shared_schema.md. Populating that database (primary-source ingestion) is out of scope for this repo — point EI_DB_URL at 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.html

Testing

.venv/bin/pytest -q

Tests 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.html

This renders the real components against committed fixtures with hot reload.

License

Apache 2.0.

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

Maintenance

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

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/crude-code/mcp-app'

If you have feedback or need assistance with the MCP directory API, please join our Discord server