mcp-app CLAUDE.md

Project instructions for an oil and gas data platform that connects an MCP server to a chat-based renderer and valuation engine.

In plain words
What is it for?
Use them when changing or extending the MCP server, renderer, or oil and gas valuation code.
Why use it?
They give the coding agent the repository structure and explain which parts handle database queries, deal forecasts, valuations, maps, and packaged procedures.

Instructions file

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/crude-code/mcp-app/claude-md
Clone the repo
git clone --depth 1 https://github.com/crude-code/mcp-app
Per session 10,942 This file is loaded in full into every session.
When invoked 10,942 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.10942 $0.10942
Opus 5 $0.05471 $0.05471
Sonnet 5 $0.02188 $0.02188
Haiku 4.5 $0.01094 $0.01094

Measured 2d ago against content hash 3be898ff390a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp-app CLAUDE.md scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

spec)` / `fetch(user_slug, token)` — synchronous, spec always in hand at
CLAUDE.md · 670 lines

How it starts

The opening of the file, as written. The whole thing — 670 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Crude Code — MCP Server & Renderer

Oil & gas data analytics platform. MCP server + spec-driven inline renderer.

Architecture

Outer Claude does the thinking; the server does deterministic work. There are no inner agents anymore — the managed-agents / inner-Opus / pip-package era was removed in the rebuild. The one exception is get_skill: a static file bundle (instructions + supporting files) Claude fetches and follows directly for occasional, procedure-heavy tasks — not an agent, no code execution on the server side. Outer Claude (in Claude Desktop / claude.ai) orchestrates everything through a handful of MCP tools:

  • It explores with run_sql (direct, capped SELECT access) right in the chat.
  • When the chat becomes a deliverable, Claude itself builds a claude.ai artifact straight from run_sql data — there is no server-side spec authoring or render step for this path anymore.
  • For deals it calls deal_forecast_wellsdeal_valuation → gets a slim payload plus the frozen DealSheet.jsx template in the same response, and builds the deal-sheet artifact from them directly.
  • For geography it calls map_render.
  • For a one-off packaged procedure (e.g. extracting a dataroom upload) it calls get_skill(name) to fetch the instructions and follows them directly.
  • When the dataroom-extract skill produces an extraction.json, it persists it via dataroom_save_extraction so the deal record outlives the chat.
  • When the user hits friction or wants something (a bug, a dataset request, a feature wish) it files message_team — durable row + best-effort email to the team.

Every tool is synchronous and server-side. The renderer today only ever renders maps: it fetches the finished, hydrated map spec once via map_read_full(token) and renders it inline — no streaming, no event log, no polling.

MCP Server (server/mcp_server.py)

FastMCP server that Claude Desktop / claude.ai connect to. Plain Python tools — no agent in the loop. Runs on port 9000 (/mcp endpoint). Per-user auth: a reverse proxy routes https://<your-host>/<slug>/mcp to the server with an X-User-Slug: <slug> header; identity resolves via the Supabase users table (utils.platform.resolve_identity).

Read the full file on GitHub · 670 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 670 lines · 10,942 tokens per session scan A 3be898ff390a

Subscribe to this mod's changes

mcp-app CLAUDE.md is an instructions file published in the GitHub repository crude-code/mcp-app (4 stars, last pushed 3d ago), licensed Apache-2.0. It adds 10,942 tokens to every session, about $0.0547 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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