"Memory" matching MCP servers:

Provides coding agents with persistent local memory by exposing tools to save, search, and retrieve decisions, bugs, and context as Markdown with hybrid keyword and semantic search.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Local, searchable project memory for AI coding agents. Markdown source of truth, MCP interface, safe structured updates

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 Agents search it before answering and save what lasts; changed facts are kept as history and flagged as outdated.

Project Memory stores decisions, evidence, outcomes and reviewed lessons in local SQLite. Assistants retrieve bounded context through three MCP tools. People follow and plan work in a live workspace with an overview, sprint board, decision history, readable documents, skills and project maps. Offline exports remain available.

A vendor-agnostic cognitive persistence layer for AI agents. Eliminate the "repetition tax" by transporting your context, preferences, and history across sessions. Features an auto-adaptation engine that syncs global instructions to ensure operational cohesion and optimize token usage across any LLM or multi-agent workflow.

MCP server for managing project memory in AGENTS.md. Allows agents to record and remove durable facts using save/forget tools.

Enables AI assistants to save resolved debugging sessions as concise experience cards into a local JSON knowledge network, and to retrieve relevant past cards when new bugs arise. It also powers a spaced-repetition review interface to reinforce memory of those experiences.

Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.

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

Automatically records AI conversation turns and code changes to local Markdown files to provide persistent context across chat sessions. It enables AI agents to search history through MCP tools and provides a web viewer for browsing past discussions.

Enables coding agents to query and modify a SQLite database through twelve SQL-based tools, with safety enforced server-side via statement policies, protected tables, result caps, and snapshots. It also provides an append-only, hash-chained memory log with checkpoints so agents can record events and resume context across sessions.

Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md

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.

Gives coding assistants a local-first SQLite store for project and global lessons with evidence, immutable replacements, retrieval tracking, and agent feedback, searched by keyword out of the box or by optional local semantic search. It runs over MCP stdio with launch-bound workspace scopes and write permissions disabled by default, so assistants can save, supersede, archive, retrieve, and rate memories entirely on the local machine.

Failure Memory provides AI coding agents with a shared local memory of failures, enabling them to record, recall, and learn from mistakes across sessions.

Provides persistent cross-session memory and full-text search for AI coding assistants, storing project context, decisions, and preferences while enabling searchable access to conversation history via local SQLite.

Provides a memory server for coding agents over MCP, capturing and retrieving the meaning and rationale behind code decisions down to the function level. It enables agents to search product memory, get task context, and propose new memories to avoid re-deriving or re-breaking past decisions.

Persistent memory and automatic git snapshots for Claude Code, capturing decisions, patterns, and architecture across sessions.

Persistent project memory for coding agents, kept in a local SQLite store with FTS5 search: search and list memories by topic, read one with its history, add a fact, show the store's statistics, and read or regenerate the PROGRESS.md handoff. Pure standard-library Python; no network.

Provides persistent local memory for AI coding sessions, enabling agents to save and retrieve project context across different tools and sessions.

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.

Enables programming agents to capture errors and conversation signals, reflect on root causes, consolidate reusable skills, and retrieve relevant context for future tasks, providing a self-learning memory loop.

Provides project memory management for Claude Desktop, storing memories as Markdown files with intelligent keyword-based retrieval and automatic creation/update decisions by LLM.

智能记忆系统，为TRAE IDE提供自动对话记录、上下文恢复和任务管理功能。

Memory for LLM agents: a local graph where the agent keeps decisions, tasks, hypotheses and reasoning between sessions, and gets a summary of what is open and overdue on every return to a project. Works with Claude Code, Codex, Cursor and opencode. Single Rust binary, no embedding model or LLM calls. Source-available (BSL 1.1), commercial use permitted.

An MCP server for persistent session context, user preferences, project conventions, and indexed state, with features like full-text search, task management, and a web dashboard.

Persists AI's cognitive fragments as a knowledge graph within each project directory, enabling project-level memory isolation and sharing via Git.

MCP server for personal and shared memory with full-text search (SQLite FTS5) and outcome tracking, compatible with any MCP agent like Claude Code, Cursor, and Codex CLI.

A portable, user-owned memory for MCP-capable agents in VS Code, enabling cross-agent recall and memory creation.