studiomeyer-memory
Provides 53 MCP tools for AI long-term memory, including Knowledge Graph construction, semantic search, contradiction detection, confidence decay, and multi-agent memory sharing. AI developers and agent builders use it to store session history, import data from other platforms, scan for secrets, and auto-consolidate learnings for persistent AI behavior across interactions.
Overview
The studiomeyer-memory MCP server implements a full suite of 53 tools for managing long-term memory in AI systems. Hosted on a GDPR-compliant Supabase EU database, it handles storage, retrieval, and analysis of AI knowledge from over 600 sessions and 1250 learnings. Tools enable persistent memory for single or multi-agent setups, with features like cross-platform history import for seamless integration.
Key Capabilities
- knowledge_graph: Constructs and queries relational graphs of learned facts and relationships.
- semantic_search: Performs meaning-based retrieval across stored memories.
- secret_scanning: Identifies and masks sensitive information in memory entries.
- auto-consolidation: Merges duplicate or related memories to optimize storage.
- session_insights: Extracts key takeaways and patterns from conversation histories.
- contradiction_detection: Flags and resolves conflicting stored information.
- confidence_decay: Reduces reliability scores of older or less-verified memories over time.
- multi-agent_support: Coordinates shared memory access among multiple AI instances.
- cross-platform_import: Loads conversation history from platforms like ChatGPT or Claude.
These tools support rapid setup in 30 seconds via MCP connection.
Use Cases
- Persistent Chatbot Development: Use session_insights and semantic_search to recall user preferences and past issues in customer support bots.
- Multi-Agent Systems: Employ multi-agent_support and knowledge_graph for teams of AI agents sharing research findings in collaborative tasks.
- Knowledge Validation: Apply contradiction_detection and confidence_decay in research AIs to maintain accurate, evolving fact bases.
- Data Migration: Leverage cross-platform_import to transfer existing AI interaction logs into a unified memory system.
Who This Is For
AI developers building stateful agents, teams creating multi-agent frameworks, and LLM integrators needing robust memory persistence without custom infrastructure.