"Information about project memory" matching MCP servers:

Provides coding agents with persistent, evidence-backed project memory and knowledge across sessions, using a structured memory tree and local knowledge base.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

MCP server providing layered, PostgreSQL-backed long-term memory for AI agents with versioned, audited writes and sensitive candidate filtering. Agents persist only explicitly requested facts, preferences, and project context via MCP tools.

Enables AI agents to persist, retrieve, and share source-linked memory across sessions via MCP tools, backed by PostgreSQL with project/session management, decision tracking, keyword search, and cross-host context handoff.

Provides persistent memory for Claude by implementing a local knowledge graph to store and retrieve entities, relations, and observations. This enables long-term information retention and personalization across different chat sessions.

Enables Claude to remember information about users across conversations by storing and retrieving data as entities, relations, and observations in a persistent local knowledge graph.

Enhanced knowledge graph memory server for AI assistants that uses Neo4j as the backend storage engine, enabling powerful graph queries and efficient storage of user interaction information with full MCP protocol compatibility.

A MCP server that provides persistent memory for AI assistants, storing personal information, relationships, and observations to enable personalized and contextual conversations.

A knowledge-graph-based memory system for AI agents that enables persistent information storage between conversations.

Slipstream - Built by Vektor Memory - a persistent multi-layered memory architecture. 4-layer associative graph memory (MAGMA) with autonomous REM cycle, CLI, DXT-MCP Cloak Tools.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Procedural memory for coding agents: not facts about the user, but how a task was solved — trigger, steps, outcome, lessons. Hooks recall it automatically; skills strengthen only on outside evidence and unused ones decay. Each memory carries its provenance and only the owner approves one as a rule. Local SQLite + FTS5, no API key, no cloud. One database for Claude Code, Codex and Cursor.

Provides AI assistants with long-term semantic memory capabilities through local vector-based storage. Enables storing, recalling, and managing information across sessions with complete privacy using ChromaDB, with no data ever leaving your machine.

MCP server for Statewave, an open-source memory runtime for AI agents. Provides persistent memory, context retrieval, and memory compilation through the Model Context Protocol.

Hand a project over — to your next session, to Cursor/Codex/Gemini, to your successor — with the reasons attached. Local-first memory MCP for coding agents: decisions re-injected before the agent acts, drift detection across every project you run. One SQLite file, nothing leaves your machine.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Persistent long-term memory for AI agents — semantic recall across Claude, Cursor, ChatGPT & MCP.

Persistent memory for AI agents with sectioned entries (project/user/context/etc), semantic search, CLI, and per-project scope. Local JSON, zero config, no server required.

Enables LLM agents to use associative memory with key/value graph-based retrieval, supporting multi-hop traversal and human-like associative leaps beyond embedding similarity.

Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.