"A server for managing memory" matching MCP servers:

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

Provides persistent session memory for AI assistants, enabling them to store, search, and retrieve conversation summaries across sessions via the Model Context Protocol.

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.

MCP server providing permanent, intelligent memory for AI coding assistants with retrieval, Hebbian learning, and governance, plus personal memory modules for accounts, habits, experiences, knowledge, and lifestyle. Enables AI assistants to recall project context across sessions and manage personal data securely.

Provides AI agents and teams with self-hosted adaptive memory, combining hybrid search and a self-improving neural memory graph to enable precise recall and serendipitous discovery across MCP-compatible clients.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

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.

Gives AI agents governed, provenance-tagged memory where facts are invalidated rather than deleted and every recall result carries validity dates, confidence, and replacement links. Stores memory in a local SQLite file with tools for remembering, recalling, invalidating, and pinning facts, plus policy enforcement and an audit trail.

A persistent, bitemporal, injection-safe memory MCP server for coding agents, offering unified retrieval across six memory layers, non-destructive belief revision, and multi-tenant namespace isolation.

Provides persistent long-term memory, knowledge base, and audit trail for AI agents, with intelligent recall, salience tracking, and CJK-aware context management.

A high-performance memory management system for AI agents with 200+ tools including 4-tier memory architecture, advanced RAG pipeline, and Git-like versioning.

A persistent, trust-scored project memory for AI coding agents, backed by PostgreSQL + pgvector, providing durable memory of architecture decisions, bug patterns, and coding conventions.

Provides AI-assisted long-term memory storage and retrieval with exact-phrase and semantic hybrid search, enabling save, read, delete, and admin recovery via MCP tools.

Enables AI agents with persistent memory using SQLite and local LLM models through Ollama integration. Provides chat with context retention and multi-client support across VS Code, Gemini-CLI, and terminal interfaces.

Provides long-term memory capabilities for Claude through persistent storage and full-text search of context across conversations. Enables storing, searching, and managing memories organized by categories like facts, preferences, projects, and goals.

A personal AI memory service based on MCP protocol that provides long-term memory capabilities for various AI clients.

MCP server that connects Claude Code to Substrate organizational memory, providing tools for searching, reading, querying, and writing memory, with automatic capture of conversation turns.

Persistent memory for Claude Code — a self-evolving knowledge layer that survives across sessions, grows from every conversation, and surfaces relevant context automatically.

A persistent, searchable memory layer for AI assistants, exposed as an MCP server. It supports CRUD, namespaces, hybrid ranked search, relationships, chat-context assembly, import/export, and optional LLM-powered auto-extraction.