"memory" matching MCP servers:

Local-first agent memory & knowledge service: hybrid retrieval (vector + BM25/RRF) + memory governance (decay, dedup, freshness), REST + MCP dual protocol, fully offline without LLM. Python.

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.

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.

Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.

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.

Provides AI agents with associative long-term memory using Sparse Distributed Memory, enabling recall from vague cues and interference detection.

A fully local persistent memory layer for LLM coding agents (Claude Code, Codex, Gemini CLI, OpenCode). A shell wrapper intercepts tool invocations, fires hooks on every tool call, then runs a 3-layer pipeline (extract → compress to ≤500-token digest → merge into project memory doc) at session end. The next session gets prior context injected automatically.

Persistent project memory for AI models and coding agents. Memory MCP stores architecture, decisions, tasks, warnings, preferences, and session state in Supabase so OpenCode, Claude Code CLI, Qwen Code, Codex, or any MCP-compatible client can resume work without losing context.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

Persistent cognitive memory for AI agents. Sub-millisecond recall, fully offline, encrypted. 8 tools: recall, recall_structured, store, store_code, store_decision, search, insights, consolidate.

Enables MCP clients like Cursor and Claude to remember user preferences and behaviors across conversations using vector search technology.

A lightweight MCP server that gives Claude Code Channels on Telegram persistent memory by storing facts, conversation logs, and session summaries in Supabase.

An MCP server that gives AI agents persistent, forgetting memory with layered decay, semantic search via token overlap, and zero external dependencies.

Flux Memory is an MCP server that provides a self-organizing weighted graph memory for AI agents, enabling persistent knowledge storage, retrieval, and feedback-based learning.

Provides MCP tools for persistent, cross-session memory via Cloudflare Agent Memory, enabling agents to store, recall, ingest, summarize, and manage memory namespaces.

A persistent, conflict-aware memory MCP server for AI coding assistants (Cursor, Claude Code).

An advanced cognitive memory agent for AI chatbots that provides long-term, autonomous memory using a four-agent system for monitoring, extraction, reconciliation, and consolidation.

Provides brain-inspired long-term memory for MCP clients, enabling persistent user understanding across sessions with Chinese-optimized hybrid retrieval and evolving user profiles.

Persistent memory storage using SQLite for AI agents to store, search, update, and manage contextual memory via the Model Context Protocol.

A generic MCP memory service that provides AI clients with long-term memory capabilities, including semantic search, categorization, and priority management. Supports both local JSON and cloud PostgreSQL storage.