CogniLayer: An MCP Server for Persistent Memory in Claude Code
CogniLayer is an MCP server built specifically for Claude Code that provides persistent memory across sessions. The tool addresses the problem where Claude Code forgets everything when starting a new session—including project architecture, past decisions, and debugging insights—forcing users to re-explain context repeatedly.
Technical Implementation
The system uses a SQLite database with FTS5 full-text search and vector embeddings (fastembed + sqlite-vec) to store knowledge locally. It implements hybrid search that combines keyword matching with semantic vector similarity.
Key Features
- Stores 14 types of facts: decisions, patterns, gotchas, error fixes, API contracts, and more
- Staleness detection: warns when remembered facts reference changed files
- Session bridges: automatically passes context between sessions
- Heat decay system: facts age over time (hot/warm/cold) with frequently accessed information staying relevant
- Identity Card system: prevents deploying to the wrong server
- 3 hooks: SessionStart, SessionEnd, PostToolUse
- 10 MCP tools and 7 slash commands
Setup and Usage
To install and use CogniLayer:
git clone https://github.com/LakyFx/CogniLayer.git
python install.pyAfter starting Claude Code in any project, run the /onboard command. The tool runs entirely locally with SQLite and works on Windows, macOS, and Linux.
The project was built using Claude Code sessions, with Claude helping design the database schema, write the MCP server, build the hook system, implement the hybrid search ranker, and iterate on the embedding pipeline. The tool is 100% free, open source under GPL v3, with UI strings currently in Czech but functional with any language.
📖 Read the full source: r/ClaudeAI
👀 See Also
Rival-Review: A Cross-Model Review Loop for AI Agent Plans
Rival-review is an MIT-licensed tool that uses a second AI model to audit plans from a primary AI coding agent before execution, catching issues like flawed rollback plans, security holes, and stale-state decisions.
TeamOut AI Agent for Company Retreat Planning
TeamOut has launched an AI agent that plans company events through conversation, handling venue sourcing, vendor coordination, flight cost estimation, itinerary building, and project management. The system uses multiple LLMs and specialized tools to manage planning as a stateful coordination problem.
Time Complexity MCP: Static Analysis Tool Feeds Big-O Complexity to AI Coding Agents
Time Complexity MCP is an open-source MCP server that performs static code analysis to detect Big-O complexity, feeding the results directly to AI coding agents like Claude Code or Copilot without token consumption. It supports JavaScript, TypeScript, Python, Java, Kotlin, and Dart.
Natural Language Autoencoders: Turning Claude's Internal Representations into Text
Transformer Circuits Thread publishes Natural Language Autoencoders that decode Claude's internal activations into readable text. GitHub repo and interactive demo available.