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    A lightweight MCP server that records and reuses prompt gaps — essential context missing from initial instructions — so your AI assistant learns from every session using a plain JSONL file tracked by Git.
    4
    6 npm
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    Enables AI agents to persist and share durable memory — appending session logs with checkpoints and handoffs, claiming and completing tasks, and recording decision records — all stored as plain Markdown and JSONL files in a git repository. Everything written is full-text searchable, and the server speaks MCP so MCP-aware clients can plug in directly with zero vendor lock-in.
    MIT
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    An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.
    21 npm
    MIT
  • A
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    Model Context Protocol (MCP) memory server built with Azure Functions and TypeScript, providing persistent knowledge graph storage for your preferred MCP client. Inspired by and forked from @modelcontextprotocol/server-memory
    3
    MIT
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    Provides a shared memory bridge for AI agents (QClaw, Claude Code, Codex) allowing them to store, search, and retrieve notes, decisions, and conclusions via MCP tools, using local SQLite with optional TencentDB integration.
    MIT
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    An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.
    MIT
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    A production-ready MCP server that enables multiple AI agents to collaborate through a shared, concurrency-safe memory space. It supports advanced search, full CRUD operations, and automatic backups to facilitate asynchronous communication between agents.
    MIT
  • F
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    Enables AI agents to share persistent memory via an MCP server using SQLite, supporting multi-tenant, categorized knowledge with TTL and semantic links, without requiring vector databases.
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  • A
    license
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    quality
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    maintenance
    Provides a shared context layer for AI agent teams to improve token efficiency through context deduplication and incremental state sharing. It enables multiple agents to coordinate tasks, share real-time discoveries, and manage dependencies while significantly reducing redundant data transmission.
    15
    0
    7
    MIT
  • A
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    maintenance
    Enables routing context and execution across AI tools like Claude, Cursor, Windsurf, and ChatGPT with a shared memory, task board, and context bus, plus local file conversion.
    12 npm
    8
    Apache 2.0
  • A
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    Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.
    Apache 2.0