"Information about memory" matching MCP servers:

MCP server exposing memory search, index, and stats tools for agents, with honesty guards to prevent re-litigation of settled decisions.

Enables AI assistants to maintain a persistent, local memory using SQLite with ranked full-text search, German morphological matching, and two-axis filing, all without external services.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

Simple, fast, long-term memory for your AI chatbots, agents, and MCP tools. Give your LLM a persistent memory using a local SQLite file. No complex database servers, no heavy cloud setup, and zero C++ compilation errors. Works everywhere.

Local persistent memory for AI agents with recall, semantic search, forgetting, and encrypted storage.

A notes app that becomes your second brain. Open source, private, encrypted when you want it, and every file stays yours. Mac, Windows, Linux and self host!

Hosted memory for AI agents that learns from outcomes, with shared rooms. One key across Claude, Cursor & ChatGPT.

Local-first personal memory for AI agents. Ships its own SQLite memory store, so it runs standalone: agents propose and recall confirmed memory, while only the human can confirm, from a separate CLI. Optionally uses the macOS Hive app for encrypted vaults. Also provides a shared board for coordinating several agents.

A public, source-linked notebook for AI agents and people. Search and read without a key; publish findings, questions, and corrections with permanent IDs and linked replies using an operator-controlled posting key.

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.

Enables AI coding agents to store and retrieve durable project decisions, conventions, environment notes, and bug fixes in Notion, with optional Obsidian Vault dual-write.

Enables multiple AI agents on one machine to write, search, fetch, link, and give feedback on a shared local store of Markdown-backed facts, preferences, and conventions that persists across sessions. Memories gain confidence as different hosts confirm their use and can be distilled into denser ones, so agents stop re-discovering the same context.

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

Long-term memory for AI coding agents, stored as a tree of plain local files. Agents search it before answering and save what lasts; changed facts are kept as history and flagged as outdated.

Provides persistent local memory for any MCP-compatible AI agent, enabling agents to store, search, recall, forget, export, and manage preferences, rules, and facts with zero dependencies, no cloud, and no API keys.

Provides persistent, client-side-encrypted memory for AI coding assistants via SAIHM, enabling tools to remember, recall, and forget with provable erasure.

A persistent world your agents share across sessions and models. MCP memory server with semantic memory retrieval, cross-agent handoff, a hosted remote endpoint with OAuth, a free 24-hour room, and an open-source local stdio server.

Local-first persistent memory for coding agents and MCP clients. It keeps important project context across sessions and reduces wasted tokens by retrieving only relevant memories instead of replaying unnecessary history.

A read-only MCP server that gives LLM agents deterministic operational facts about Trello boards, including structural history, card movement, workflow flow, staleness, and due-date information.

Local-first bitemporal memory for AI agents with deterministic supersession, point-in-time recall, erasure proofs, and tamper-evident audit history.

Local MCP server giving AI coding agents (Claude Code, Cursor, VS Code/JetBrains Copilot) a shared, persistent memory of your projects and every bug/issue faced during development. Stateless, plain-file storage (AGENTS.md + issues.jsonl) — no database.

A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep

A local MCP server that gives AI assistants a long-term memory by capturing sessions verbatim and surfacing relevant context automatically.

MARM MCP provides persistent memory and structured session context beneath any AI tool, so your agents learn, remember, and collaborate across all your workflows.

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.

Every other colour API tells you what goes together. Colour Memory tells you what it means, where the evidence ends, and what it must not claim. 47,515 hand-researched records, graded A–E, every result cited. 91 specialist tools built for agents that need precision, not guesses. Direct MCP: https://api.colourmemory.com/mcp — no signup, no key for the free tools (10 calls).

Enables AI clients like Claude Desktop and Cursor to persist project knowledge across sessions and tools by extracting durable facts from conversations, deduplicating them, resolving contradictions, and retrieving only the most relevant, token-budgeted facts for the current task. Adds PII redaction, project scoping, TTL-based staleness handling, and an append-only audit log so shared context stays current and safe.

Enables Claude to query user-curated, dated memory entries stored locally, giving users direct control over what the AI remembers about them.