MCP servers for long-term memory and vector search: store notes, embeddings and facts so an AI assistant remembers across sessions. 799 servers in this category.
Provides a local-first persistent memory layer that allows different AI agents to share project-specific knowledge and work journals.
$claude mcp add ai-agent-memory-mcp -- uvx ai-agent-memory-mcp
Provides a tiered, Markdown-backed hybrid memory system for AI agents with decision tracking and multi-tenancy support.
Provides AI coding agents with a persistent, local, repository-aware memory layer using SQLite to store project rules, corrections, and architectural decisions.
$claude mcp add repo-memory-mcp -- uvx repo-memory-mcp-ai
Lets AI agents on multiple machines share a synced, searchable memory journal without a central server.
Enables AI clients to perform local vector storage, document ingestion, and semantic search using FAISS for Retrieval-Augmented Generation.
$claude mcp add local-faiss-mcp -- uvx local-faiss-mcp
Gives AI clients and IDEs a persistent shared memory layer to save, search, and retrieve documents and facts across sessions.
$claude mcp add --transport http memwyre https://server.memwyre.tech/mcp/
Provides a local-first memory infrastructure for AI agents using hybrid vector, lexical, and graph retrieval.
Provides AI agents with a persistent, graph-based long-term memory framework using SQLite or Neo4j to store entities, observations, and relationships.
Provides a self-hosted, two-tier knowledge graph memory for AI agents using Graphiti and FalkorDB over a private Tailscale network.
Provides a memory engine for AI agents featuring vector search, knowledge graphs, and hybrid retrieval.
Provides persistent long-term memory for Claude Code and MCP clients using hybrid BM25, vector, and knowledge-graph search over Markdown files.
Provides shared project memory for AI agents with source-backed facts, reviewable updates, and verifiable citations.
Provides local-first neural memory for AI agents by indexing Markdown vaults with lexical, semantic, and knowledge-graph search capabilities.
Provides user-owned, cross-agent AI memory using a local SQLite database and Gemini embeddings to enable persistent context across different AI clients.
Provides persistent, shared memory for AI agents using a plain-markdown Obsidian vault with hybrid search and a browsable knowledge graph.
Provides a persistent, local, CPU-only memory system for AI agents using hybrid retrieval and automated consolidation.
Provides embedded, local-first memory and hybrid retrieval for AI agents using a single SQLite file.
$claude mcp add rmbr -- uvx rmbr
Provides a bi-temporal knowledge graph and token-budgeted context compiler to give AI coding agents persistent, conflict-aware memory.
Provides AI agents with persistent memory using hybrid vector search, full-text retrieval, and a knowledge graph backed by PostgreSQL.
Provides persistent SQLite-based episodic memory and semantic knowledge graphs to give AI agents cross-session recall and context.