MCP-Memory

ai-memory is an open-source local server for long-term memory and session handoff among AI coding agents. It captures prompts, tool calls, and agent context through MCP integrations and lifecycle hooks, storing the material in a searchable, Git-backed Markdown wiki. When a session ends or is explicitly finalized, it generates handoff context for a subsequent session, including the project architecture, failed approaches, and open questions, so work can continue across agent vendors without restating the context; clients without a true session-end hook use explicit finalization commands. The project documents integrations for Claude Code, Codex, Command Code, Devin CLI, OpenCode, Cursor, Gemini CLI, Oh My Pi, Pi, and Crush, with agent-specific configuration, generated plugins or extensions, and capture exclusions. It runs on Linux, macOS, and Windows through WSL2, with experimental native Windows support, and is distributed through Docker images and native release binaries.

codebase-memory-mcp is an MCP server from DeusData that indexes a codebase into a persistent local knowledge graph for AI coding agents. It parses source with tree-sitter AST grammars and uses Hybrid LSP semantic type resolution for selected languages to model functions, classes, call chains, HTTP routes, and cross-service links. Its MCP tools support code search, structural and Cypher-style queries, call tracing, architecture overviews, impact analysis, dead-code detection, and graph visualization. The project is distributed as native executables for macOS, Linux, and Windows, with no language runtime, hosted service, or API key required. Processing is local; the repository describes a RAM-first pipeline using compressed data, in-memory SQLite, and fused Aho-Corasick pattern matching, and reports sub-millisecond structural queries. A local visualization interface is available at localhost:9749.

agent-memory is a local-first, agent-agnostic long-term memory runtime for AI agents. It stores memories as plain Markdown files, with a rebuildable SQLite index used as a cache rather than the source of truth. Conversation-boundary hooks trigger writes, while an independent sleep-time Manage pass consolidates, ages, and forgets memories by value; unattended deletion is limited to proposals that require confirmation, and superseded or archived material remains available. The runtime provides three recall paths: deterministic MEMORY.md injection at session start, BM25 search with progressive disclosure, and direct access through the store's directory tree using tools such as ls and grep. Memory records use frontmatter for names, abstracts, status, timestamps, links, weights, and provenance, with free-form Markdown bodies. Its CLI, MCP server, and host-agent hooks share the same validation, hash-diff, and reindexing path, and it can be used by agents that run shell commands, including Claude Code and Codex CLI. The repository documents a Python 3.12-or-later setup using uv, commands for initialization, recording, recall, rebuilding, sleep-time consolidation, and proposal approval, plus host setup for Claude Code and Codex. It does not include an LLM client; reasoning is delegated to the host agent's CLI, so the library requires no separate model keys or billing surface.

Claude-Mem is an open-source persistent-memory plugin and service for coding agents. It captures agent activity through lifecycle hooks, stores sessions, observations, and summaries in SQLite, and uses hybrid full-text and Chroma vector search to retrieve relevant context across sessions. Its MCP search workflow uses progressive disclosure: the agent first searches a compact index, then reviews a timeline, and finally fetches full observations for selected result IDs. A local worker service, managed by Bun, provides the HTTP API, search endpoints, and web viewer; the project also supports integrations with Claude Code and other listed agent environments, configurable context injection, private-content exclusion tags, and optional cloud synchronization. The repository states that it is distributed under the Apache License 2.0 and requires Node.js 20 or later, with Bun, uv, and SQLite used by the runtime. It can be installed through its npx installer or Claude Code's plugin marketplace.

Supermemory is an AI memory and context engine with a hosted API, application, plugins, MCP server, and local runtime. It extracts facts from conversations, tracks temporal changes and contradictions, automatically forgets expired information, and maintains user profiles containing stable facts and recent activity. Its API combines memory retrieval with hybrid RAG search, allowing applications and AI agents to query personalized context and knowledge-base documents together. It also processes uploaded PDFs, images, videos, and code, and can synchronize data from services such as Google Drive, Gmail, Notion, OneDrive, GitHub, and web pages. SDKs are available for JavaScript and Python, with integrations for AI frameworks including the Vercel AI SDK, LangChain, LangGraph, OpenAI Agents SDK, Mastra, Agno, and n8n. Supermemory can provide persistent memory to compatible assistants through plugins or its MCP server. The local distribution runs as a single binary or through npx, uses local embeddings by default, supports OpenAI-compatible and Ollama-backed models, and exposes the same Memory API on localhost for offline or self-hosted use.