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Capture knowledge and inject guardrails for AI coding assistants automatically.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "brain-mcp" yet — see the docs or source repo.
Please capture recurring coding conventions, folder rules, and common mistakes from this repository and turn them into knowledge and guardrails for Claude and Cursor.
Reusable project knowledge and constraints that help AI assistants follow team conventions in future code generation.
Based on issues found in recent code changes, add guardrails for the AI assistant to avoid making the same mistakes again.
Guardrail rules targeting common errors, reducing the chance of repeated mistakes in later AI-generated code.
Set up automatic knowledge capture and guardrails for this codebase so Cursor prioritizes existing practices when generating code.
AI assistants follow established patterns more closely, improving consistency and code quality.
Development teams using Claude or Cursor over time can use it to capture project knowledge and constraints automatically. This helps the assistant follow team standards with less repeated prompting.
When an AI assistant keeps making similar mistakes, injected guardrails can reduce those repeats. It fits engineering workflows focused on better code quality and consistency.
It automatically captures knowledge and injects guardrails for AI assistants such as Claude and Cursor. Its goal is to improve code quality and prevent recurring mistakes.
The provided description explicitly mentions Claude and Cursor. For support of additional assistants, see the source repository.
The provided material does not include installation steps, runtime requirements, or API key details. For prerequisites and setup, see the source repository.
Give AI coding assistants local long-term memory with searchable lessons and patterns.
Sync Gmail, Drive, and Calendar locally for search and context retrieval.
Provides shared persistent knowledge-graph memory across Claude installations with concurrent access.
Give AI coding agents long-term memory, search, and organization across sessions.
Give AI coding assistants persistent, conflict-aware memory across projects and sessions.
Persist, consolidate, and manage AI conversation memory across storage backends.