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.
npx agentmods add instructions/adamsmaka/flutter-mcp/claude-mdgit clone --depth 1 https://github.com/adamsmaka/flutter-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/adamsmaka/flutter-mcp/claude-md)<a href="https://agentmods.dev/instructions/adamsmaka/flutter-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/adamsmaka/flutter-mcp/claude-md.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00646 | $0.00646 |
| Opus 5 | $0.00323 | $0.00323 |
| Sonnet 5 | $0.00129 | $0.00129 |
| Haiku 4.5 | $0.00065 | $0.00065 |
Grade A, and why
flutter-mcp CLAUDE.md scanned grade A with 0 findings 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 6d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
This is a Flutter/Dart documentation MCP (Model Context Protocol) server project designed to provide AI assistants with seamless access to Flutter and Dart documentation. Following Context7's proven approach, the project uses on-demand web scraping with Redis caching to ensure users always get the most current documentation while maintaining fast response times.
Key Architecture Components
- MCP Server: FastMCP server with on-demand documentation fetching
- Redis Caching: Fast in-memory cache for processed documentation
- Web Scraping: Respectful fetching from api.flutter.dev and api.dart.dev
- Pub.dev API: Official API for package documentation
- Processing Pipeline: Parse → Enrich → Clean → Cache (Context7-style)
- Rate Limiting: 2 requests/second to respect server resources
Development Commands
# Project setup (using uv package manager)
uv init mcp-server-flutter-docs
cd mcp-server-flutter-docs
uv add "mcp[cli]" httpx redis beautifulsoup4 structlog
# Start Redis (required for caching)
redis-server # In a separate terminal
# Development server with MCP Inspector
mcp dev server.py
# Run the server
uv run server.py
# Alternative with traditional Python
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install "mcp[cli]" httpx redis beautifulsoup4 structlog
python server.py
Core Implementation Guidelines
- On-Demand Fetching: Fetch documentation only when requested, like Context7
- Redis Caching: Cache processed docs with appropriate TTLs (24h for APIs, 12h for packages)
- Smart URL Resolution: Pattern matching to resolve queries to documentation URLs
- Rate Limiting: RateLimiter class ensuring 2 requests/second max
- Error Handling: Graceful fallbacks when documentation isn't found
- User Agent: Always identify as "Flutter-MCP-Docs/1.0" with GitHub URL
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.
- 6d ago First seen · 65 lines · 646 tokens per session scan A 2ee37c2b2389
flutter-mcp CLAUDE.md is an instructions file published in the GitHub repository adamsmaka/flutter-mcp (73 stars, last pushed 9mo ago), licensed MIT. It adds 646 tokens to every session, about $0.0032 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.