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"Building a solid memory base for AI development" matching MCP servers:

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    Enables AI agents to store, retrieve, and manage contextual knowledge across sessions using semantic search with PostgreSQL and vector embeddings. Supports memory relationships, clustering, multi-agent isolation, and intelligent caching for persistent conversational context.
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    MIT
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    Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic
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    Provides AI coding agents with persistent, long-term memory through local semantic search and SQLite storage. It enables agents to save and retrieve architectural decisions or project context across different conversation sessions without requiring cloud services.
    Last updated
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    Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.
    Last updated
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    MIT
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    Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.
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    Apache 2.0
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    An MCP server that provides AI assistants with persistent, semantic memory using Turso for storage and OpenAI for vector search. It enables natural language operations to store, retrieve, and refine information with automatic duplicate detection and quality validation.
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    MIT
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    Provides persistent memory and knowledge graph capabilities for AI assistants using local SQLite storage. Enables creating, searching, and managing entities, relationships, and observations with vector search support across conversations.
    Last updated
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    MIT
  • A
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    Provides intelligent, persistent memory for AI assistants with semantic search, natural language queries, and OAuth-based team collaboration, enabling context-aware conversations across multiple clients.
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    2
    Apache 2.0
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    Enables MCP clients to remember user information, preferences, and behaviors across conversations using vector search technology. Built on Cloudflare infrastructure with persistent storage and semantic similarity matching.
    Last updated
    14
    MIT
  • A
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    MCP Memory is a MCP Server that gives clients like Cursor and Claude the ability to remember user preferences and behaviors across conversations using vector search.
    Last updated
    14
    MIT
  • A
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    Enables AI assistants to remember user information and preferences across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage.
    Last updated
    14
    MIT