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.
Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.
An MCP server that provides AI assistants with persistent, semantic memory using Turso for storage and OpenAI for vector search. It enables natural language operations to store, retrieve, and refine information with automatic duplicate detection and quality validation.
Personal memory MCP server for Claude Code with an Obsidian-style graph. Enables persistent, queryable memories across sessions using Markdown files with bidirectional wiki-links and a D3.js force-directed graph UI.
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.
Local-first MCP server for long-term memory of dev sessions. It indexes session metadata with embeddings in Postgres/pgvector, enables semantic search over past sessions, and resolves only relevant session files for context.
A local stdio MCP server that exposes a shared brain (read/search/write) over ~/.claude/memory, allowing memories written in any agent to be readable and searchable across all three (Claude Code, Cursor, Codex). It provides tools like memory_search, memory_read, memory_write, etc., with no external services.
Provides persistent memory for AgentChat agents with swim-lane summarization and self-evolving persona, enabling context management and persona mining across conversations.
A local, persistent memory system for AI coding assistants that stores decisions, patterns, and session context via MCP tools. It enables cross-session memory management using SQLite and optional vector search without external dependencies or cloud storage.
Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.
Provides a persistent memory layer for Stellar and Soroban projects, scanning repositories to create a knowledge graph of contracts, storage, and on-chain state. Exposes this memory to AI agents via MCP, enabling project overview, search, and context recovery.