Long-Term Memory for AI Agents

agentmemory gives AI coding agents persistent, searchable context from earlier work. It's for developers who want project decisions, past errors and useful lessons to remain available across sessions and different agents.

Codebase Memory MCP maps a repository's structure so AI coding agents can explore dependencies without repeatedly reading whole files. It's for developers using Claude Code, Codex CLI, Cursor or other MCP-compatible clients.

ECC adds reusable engineering workflows to AI coding assistants. It's for developers who want editable plans, test-first development and separate review contexts across sessions.

Claude Mem gives coding assistants persistent project memory, so developers can carry earlier decisions and failed approaches into later sessions without explaining them again.

FalkorDB is a self-hosted graph database for developers building GraphRAG applications and AI agents that retrieve connected facts. It stores entities, relationships and their attributes, with Cypher queries and vector search for finding relevant information. Docker runs the database on your own hardware; a separate hosted cloud service is also available.

Exo Agent Framework is for developers building long-running AI agents that can revise their own code, tools and prompts. It preserves agent identity and history as their behavior changes across runs.

HarnessX is a Python framework for developers building AI agents whose behavior they can reuse and adapt. It separates model choice from tool use, memory and context handling, so changing an agent's role doesn't require rewriting it.

Paxm gives AI coding assistants persistent memory of project decisions, conventions and past work. It's for developers who want later sessions or another coding agent to recover context they've already explained.

Captain Memo gives developers a shared memory across coding assistants, so project decisions and lessons remain available between sessions and tools. Claude Code, Codex, Gemini CLI, Cursor and other MCP-compatible assistants can access the same corpus.

iAi Personal Memory Engine gives AI assistants persistent memory on your machine. It's for people using coding agents who want past conversations, project details and preferences available across sessions.

Pathrule gives AI coding agents project knowledge that stays attached to the relevant workspace and file paths. Memories, rules and skills can follow a repository across agents and sessions, so developers can retain decisions and constraints without pasting the same instructions into each conversation.

memU gives connected AI agents a shared memory of preferences, project decisions and learned workflows. It's for people who move between agents or sessions and want useful context to carry into later tasks.

next-wiki is a self-hosted wiki for people and teams who want AI-assisted knowledge management with a record of where information came from. It keeps original sources separate from AI-written material and reviewed pages, so an assistant's synthesis remains traceable to its evidence. It's open source under Apache 2.0 and runs as a browser app on your own Docker host with PostgreSQL.

Link gives AI agents persistent memory so you don't have to repeat preferences, project decisions and context in every session. Multiple agents can read the same local Markdown files, which you can inspect in an editor or Obsidian.

Waku Agent is a personal AI assistant that runs on your laptop, stores its memory locally and calls remote model providers. It's for developers who want to inspect and change the assistant's behavior in Python. The agent uses provider API credentials for reasoning; requests to cloud providers are processed by those services.

HippoRAG is a Python memory and retrieval framework for developers building LLM applications that need to connect facts across documents. It uses a knowledge graph to find related information for questions that require several pieces of evidence.

Cognee gives AI agents memory across sessions so they can reuse project context, decisions, and lessons from earlier work. It's for developers building agents and teams whose knowledge sits across documents, code, and conversations.

LangGraph is an AI agent framework for developers building applications on their own machines, including workflows that use local models through LangChain's ChatOllama integration. Ollama can run models such as gpt-oss locally. LangGraph also works with remote model providers, so where model requests go depends on the connection your application uses.

Hypha is a TypeScript AI agent framework for developers building applications that need controlled tool use and recoverable work. It separates an agent's planning and tool choices from the execution layer that decides which actions may proceed.

Project Orchestrator coordinates AI coding agents for developers working across tasks or related repositories. It gives agents a shared record of code, plans and decisions so each task can draw on earlier work.

SpecStory saves AI coding conversations so developers can recover decisions, find past solutions, and carry context into another task. Its CLI and editor extensions keep session history locally across projects and coding tools.

XERJ is a local search engine for developers building AI agents that need to retrieve code, documents or stored knowledge without reading whole files into their context. It runs on a laptop or self-hosted server.

SimpleMem is a memory system for developers building AI agents that need to recall past conversations and stored media without passing the full history to a model each time.

Magic Context is a memory and context plugin for developers using OpenCode, Pi and OMP. It carries project knowledge across sessions and compresses older conversations in the background to avoid interrupting the agent's work.

Engram keeps project knowledge between coding sessions so developers don't have to repeat past decisions, bug fixes, and conventions to their AI agent. It works with existing coding assistants through MCP.

Understory gives AI agents persistent knowledge across sessions in Markdown files you can read, edit, and track in Git. It's for people who want their agents' memory accessible outside a chat history.

unleashd, listed as Buddies in its repository, is a local workspace for developers coordinating multiple coding agents. It keeps each agent's identity and memory across conversations, so a team can continue work with earlier context.

Polywise is a self-hosted system for people who want AI agents to work with saved research, notes, and project context. It keeps that material available across conversations so you don't have to explain the same work each time.

Context+ is a local MCP server for developers who want coding assistants to find relevant code and understand the effects of a change across a large project. It works with Claude Code, Cursor, VS Code, Windsurf and OpenCode.

MCP Reference Servers gives developers examples for connecting AI applications to tools and data. Maintained by the MCP steering group, these are educational implementations, not production-ready servers.

Screenpipe records computer activity so people can revisit past work and give AI agents context from screens and conversations. Capture history stays on your device by default.

OpenLore helps developers keep AI coding agents grounded in large or unfamiliar repositories. It maps code relationships and retains architectural decisions so agents can find relevant context and check proposed changes.

Obelisk makes past coding agent sessions searchable for developers who need to recover decisions or revisit earlier work. A desktop browser and an agent skill give people and coding assistants access to the same local history.

llmwiki-cli gives AI agents a local Markdown wiki for building and maintaining a personal knowledge base. It's for people who want an agent to organize their information while keeping the wiki files on their own machine.