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"Information and resources about memory" matching MCP servers:

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    A MCP Server that gives AI assistants the ability to remember information about users across conversations using vector search technology.
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    Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.
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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.
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    Enables AI assistants to remember and retrieve user information across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage.
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    Enables AI assistants to remember user information across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage and retrieval.
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    Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.
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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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    A self-organizing, persistent semantic memory layer that enables AI agents to store, categorize, and retrieve information using hybrid vector and keyword search. It features autonomous chunking, deduplication, and hierarchical taxonomy management through a PostgreSQL-backed MCP server.
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    A Rust-based MCP server that provides long-term memory capabilities for AI agents using keyword-based storage and retrieval. It supports isolated namespaces for different users or projects, allowing LLMs to remember and recall information across sessions.
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    • Apple
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    Memory Bank Server provides a set of tools and resources for AI assistants to interact with Memory Banks. Memory Banks are structured repositories of information that help maintain context and track progress across multiple sessions.
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    Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.
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    Provides persistent AI agent memory using a local vector database for long-term semantic storage and short-term session scratchpads. It enables low-latency memory operations including search, storage, and bulk management without external cloud dependencies.
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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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    An MCP server that stores project memory in Supabase, allowing AI tools to persist context, notes, and decisions across sessions. Enables Claude Code, Codex, and similar assistants to maintain long-term project continuity through persistent memory storage.
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    MIT
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    A local, persistent memory system for AI coding assistants that stores decisions, patterns, and session context via MCP tools. It enables cross-session memory management using SQLite and optional vector search without external dependencies or cloud storage.
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    An intelligent personal CRM that processes WhatsApp conversations to build a searchable knowledge base about contacts using diarization, transcription, and PII sanitization. It exposes MCP tools for semantic search, contact summaries, and reminder management within Claude Desktop.
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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.
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    MIT
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    AI memory server with 53 tools. Knowledge Graph, semantic search, session tracking, multi-agent support.
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    MIT
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    A drop-in replacement for Anthropic's memory server that utilizes SQLite to ensure data integrity and concurrent access. It enhances the original functionality with semantic search capabilities using vector embeddings and ONNX models.
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    Persistent memory and handoff intelligence layer for MCP agents. Most memory servers retrieve text — Memory Nexus compounds operational context, learning from usage and progressively synthesizing observations into higher-order intelligence across sessions and tools.
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    MIT
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    Provides persistent long-term memory for AI coding agents by storing entities, relations, and observations across different sessions. It enables users to manage and query structured knowledge like coding preferences, project patterns, and technical solutions via a graph-based storage system.
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    Enables access to Usage and Billing APIs for managing accounts, products, meters, plans, and usage reporting. Supports operations like creating products/plans, reporting usage, and retrieving billing information.
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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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    • Apple
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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.
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    A Model Context Protocol server that provides AI assistants with persistent semantic memory and knowledge graph capabilities using PostgreSQL and vector embeddings. It enables cross-session storage, hybrid search, and complex relationship tracking for enhanced contextual awareness.
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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 AI-powered semantic search to find relevant memories based on meaning rather than keywords.
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    Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md
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    • Apple
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    Enables Claude to maintain persistent memory across conversations using a local knowledge graph with fuzzy search capabilities, allowing it to remember and recall information about users, relationships, and context.
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    A persistent memory system using a local knowledge graph that enables Claude to remember information about users across chats, with advanced search, graph traversal, and filtering capabilities for entities, relations, and observations.
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    MIT
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    Persistent memory for any AI assistant. Zero token cost until recall. Stores memories in local SQLite, ranks by 6-factor scoring, returns results 79% smaller than JSON. Works with Claude, ChatGPT, Grok, Cursor, Windsurf, and any MCP client.
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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
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