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"A server for managing memory" matching MCP servers:

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    An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.
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    27,145
    MIT
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    Provides persistent, decay-aware memory for AI applications by integrating the Smara Memory API through semantic search and Ebbinghaus forgetting curves. It enables tools to store, search, and manage long-term user context with importance-based ranking and automatic decay.
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    MIT
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    Provides persistent session memory for AI assistants, enabling them to store, search, and retrieve conversation summaries across sessions via the Model Context Protocol.
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    MIT
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    A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.
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    MIT
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    Provides persistent memory storage with advanced features like tagging, content search, and expiration settings. It enables users to create directed links between stored memories to build structured relationships and knowledge graphs.
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    ISC
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    A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.
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    101,844
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    MIT
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    A Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.
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    A customized MCP memory server that enables creation and management of a knowledge graph with features like custom memory paths and timestamping for capturing interactions via language models.
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    MIT
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    A Model Context Protocol server that provides persistent memory capabilities for AI systems, enabling true continuity of consciousness across conversations through episodic, semantic, procedural, and strategic memory types.
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    A Model Context Protocol server that reduces token consumption by efficiently caching data between language model interactions, automatically storing and retrieving information to minimize redundant token usage.
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