Brain-MCP Developer Documents Tools for Claude AI Instead of Humans
A developer maintaining the Brain-MCP server, which gives Claude memory across conversations, discovered that the primary consumer of their documentation was Claude rather than human GitHub readers. They added a "For AI Assistants" section at the top of the README containing behavioral instructions rather than just tool descriptions.
Key Details from the Experiment
The developer created a dedicated page at brainmcp.dev/for-ai with specific guidance for AI assistants. The behavioral instructions in the README function like a system prompt for tool usage.
The immediate difference observed was that Claude started using tools more intelligently—not just when explicitly asked, but proactively injecting relevant context when the user switched topics.
Documentation Pattern for AI Consumption
The developer suggests that if your MCP server is consumed by an AI, you should write documentation specifically for the AI. This includes:
- Not just tool names and parameter types
- Actual guidance on when and how to use tools effectively
- Behavioral instructions that influence how Claude uses the tools
Specific Examples from the Documentation
The documentation includes practical guidance such as:
- When to proactively search (e.g., when user says "where did I leave off" → call tunnel_state)
- How to present results ("synthesize, don't dump raw search results")
- When NOT to search (pure commands, continuation of same thread)
Technical Details
The Brain-MCP server can be installed with: pipx install brain-mcp && brain-mcp setup
The project includes 25 tools, is 100% local, and is MIT licensed.
The developer is asking other MCP developers if they've experimented with similar approaches to influence how Claude uses their tools beyond basic tool descriptions.
📖 Read the full source: r/ClaudeAI
👀 See Also
Claude Proposal: Scope Memory & Hermetic Instance Isolation
A formal proposal to Anthropic from a power user: global/local memory scoping and hermetic instance isolation for Claude, enabling deterministic, auditable sessions.
SIDJUA V1.0: Self-Hosted Governance Platform for AI Agents
SIDJUA V1.0 is a free, self-hosted governance platform for AI agents that runs on Docker, including Raspberry Pi. It provides mandatory checkpoints for agent tasks, encrypted credential storage, network isolation, and granular budget controls.
Fullerenes: Open-source persistent memory layer for coding agents cuts tokens by 64% on SWE-bench
Fullerenes uses a local SQLite knowledge graph built via Tree-sitter to give coding agents like Claude Code persistent memory, reducing token usage by 64% on SWE-bench and up to 96.6% on internal benchmarks.
Forge: A Memory System for Claude Code Built with Claude Code
A developer built Forge, a TypeScript monorepo MCP server that automatically captures decisions, constraints, and rejections from Claude Code conversations. It uses a six-stage pipeline to classify, extract, and persist structured data in an event-sourced SQLite model.