Self-hosted AI agent memory server with MCP, evidence provenance, typed claims, conflict detection, embeddings, recall, PostgreSQL, and pgvector

Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.

Open-source self-hosted AI agent runtime and multi-agent framework for autonomous agent swarms. Agent memory, MCP tools, schedules, delegation, and 23+ LLM providers (Claude, GPT, Gemini, OpenRouter, Ollama). A practical Claude Code and LangChain alternative.

Correction-first persistent memory for AI agents. MCP server + SDK + CLI. Compounds across sessions.

A selective learning and memory substrate for agentic systems — typed, revisable, decayable memory with competence learning and trust-aware retrieval.

Memory service, SDK, CLI, and plugins for agent recall and writeback.

DevContext is a cutting-edge Model Context Protocol (MCP) server designed to provide developers with continuous, project-centric context awareness. Unlike traditional context systems, DevContext continuously learns from and adapts to your development patterns and delivers highly relevant context providing a deeper understanding of your codebase.

Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.

Cofounder is a project harness that turns your AI coding agent into a technical cofounder.

Lightweight agent orchestration dev tool that lives in your repo

MCP server for external memory layer for AI agents + more . Download from pypi , and get started

Universal memory runtime for AI agents

Causal memory layer for AI agents — MCP server that records decision→outcome relationships. Survives compaction.

Your durable workspace across AI agents.

Shared Memory Storage for Multi-Agent Systems

Shared context, memory, and task coordination across AI coding agents. Single Go binary, local SQLite, hybrid keyword and semantic search.

Git-native memory for coding agents. Repo memory before the diff.

Persistent Claude Code agents with scheduling, sessions, memory, and Telegram.

One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

Zettelkasten-based persistent memory for AI coding agents. Works with Claude Code, Cursor, VS Code Copilot, Codex, Windsurf & any MCP client. No vector DB — just markdown + git sync.

The Cursor10x MCP is a persistent multi-dimensional memory system for Cursor that enhances AI assistants with conversation context, project history, and code relationships across sessions.

Portable project memory across Claude Code, Codex and OpenCode, plus token accounting measured from harness transcripts. Local file I/O, no API calls, no telemetry.

A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown and Milvus.

Tool-to-Agent Protocol: tools can be smart without embedded LLM calls.