Crude Code — MCP server & spec-driven inline renderer for oil & gas data analytics
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 runsql data, or from runvaluation'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.
Path What it is ------------------ server/ FastMCP server (mcpserver.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, map handle store, identity, logging tests/ Pytest suite covering the tools, engine, maps, and guards
See CLAUDE.md for the full architecture reference.
- runsql — guarded, SELECT-only, capped exploration query - forecastwells / runvaluation — well-decline forecasting and economics, returning the data behind a claude.ai deal-sheet artifact - map — a MapLibre GL well/unit/PLSS map - getskill — fetches a packaged, occasional-use procedure (e.g. dataroom extraction) - savedataroomextraction — persists a dataroom extraction so the deal record outlives the chat - messageteam — files bugs, feedback, and data requests to the te
From the project README.
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Stop your AI from making things up — it proposes, deterministic tools decide, every claim checked against ground truth with evidence. Grounded facts and context survive resets. Reverse engineering is
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