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"Information about SQLite databases" matching MCP servers:

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    A zero-config MCP server that enables AI to access, analyze, and manage local SQLite databases with secure read-only querying and automatic schema discovery.
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    MIT
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    Provides comprehensive SQLite database interaction for AI agents, including data manipulation, schema inspection, and automated query logging. It features a unique context preservation pattern that uses a dedicated meta-table to help autonomous agents maintain self-documenting database architectures.
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    MIT
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    Provides persistent memory, skill tracking, failure indexing, and context sharing for Claude Code using SQLite with FTS5 full-text search.
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    A graph-friendly relational server that stores project memory, tasks, and metadata in a centralized SQLite database as the authoritative source of truth. It enables AI agents to manage complex project states through entity-relationship modeling and can generate human-readable markdown views on demand.
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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.
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    MIT
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    A personal knowledge graph and memory system for AI assistants using SQLite with FTS5 full-text search, enabling persistent memory across conversations with Claude or any MCP-compatible AI.
    2
    MIT
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    Provides read-only Arknights intelligence over MCP, enabling structured queries about stages, enemies, operators, and modules with region tagging and evidence-backed analysis. It uses versioned SQLite snapshots and never fetches upstream data at query time.
    13
    Apache 2.0
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    A local MCP server that maintains a persona profile (contact library) for AI assistants, allowing them to create, search, retrieve, supplement, and correct information about people mentioned in conversations via tools like search_profiles, get_profile, create_profile, update_profile, add_facts, update_fact, and delete_fact.
    8
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    Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.
    10
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    MIT
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    A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep
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    MIT
  • A
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    Local-first MCP memory server that gives AI coding agents long-term memory via SQLite and sqlite-vec, with optional LLM-powered layering. No gateway or API key required.
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    4
    MIT
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    Persistent memory for AI coding agents, storing learned architecture decisions, patterns, and bug fixes in a local SQLite database with full-text search, enabling agents to recall information across sessions.
    6
    631
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    MIT
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    An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.
    4
    48
    MIT
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    A local, fully-offline MCP memory server that enables persistent storage and retrieval of information using SQLite with both keyword and semantic vector search capabilities.
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    MIT
  • F
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    A knowledge graph memory server using SQLite to provide persistent, isolated contexts for organizing information into searchable categories like work and personal projects. It features unique ID-based operations and a token-efficient serialization format designed to optimize interactions with LLMs.
    11