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"Multi-Agent Systems with Shared Memory Storage" matching MCP servers:

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    A portable, self-hosted semantic memory layer for LLM agents, enabling them to search and add memories by meaning over the Model Context Protocol.
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    MIT
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    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.
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    MIT
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    MCP server providing persistent memory management for AI agents using SQLite and FTS5, enabling storage, full-text search, and recall of memories with namespace isolation.
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    MIT
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    An MCP server that exposes web lookup, save note, and list notes tools for a router-research-writer agent pipeline, enabling coordinated multi-agent workflows via the Model Context Protocol.
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    MIT
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    Agent-native object storage MCP server with per-agent DID isolation and x402 pay-per-byte metering in real Base USDC, enabling autonomous agents to store and retrieve objects with hot, warm, or cold retention classes.
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    MIT
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    MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.
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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.
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    Shared Margin is a Codex-native room for reading books and watching films together one moment at a time. It enables human and GPT-5.6 to linearly experience media, capture anchored observations, and maintain a durable trail.
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    5
    MIT
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    An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.
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    MIT
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    Standalone memory microservice that converts completed agent sessions into long-term memory and exposes retrieval through an MCP tool interface, enabling agents to search their past interactions.
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    MIT
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    MCP server for zero-config, traceable long-term memory using SQLite, enabling agents to store, search, trace, and monitor memory with tools like memory_store, memory_search, and memory_health.
    Last updated
    MIT