"SimpleX" matching MCP servers:

Provides AI coding agents with persistent memory by recording sessions and normalizing them into a searchable knowledge graph, then delivering relevant context at the start of the next session.

An MCP server that tracks AI prompts in Claude Code and automatically annotates git commits with the history of what was asked. It provides tools to query session summaries, retrieve uncommitted work, and manage AI provenance directly within Claude.

Provides AI assistants with persistent memory across sessions using local SQLite and keyword search, allowing storage and retrieval of user preferences, project context, and decisions.

Enables AI assistants to store and retrieve persistent memories with a web management interface. Supports creating, searching, and managing memories through natural language commands or a visual web dashboard.

Personal memory MCP server backed by SQLite FTS5 BM25 search with temporal reranking.

Self-hosted knowledge manager and MCP server that lets you organize snippets, questions, and documents via a web UI and exposes them to AI assistants for reading and writing.

An MCP server that extends AI agents' context window by providing tools to store, retrieve, and search memories, allowing agents to maintain history and context across long interactions.

Enables LLMs to store, search, and manage memories with hybrid semantic and keyword search using ChromaDB and Neo4j for persistent memory and knowledge graph capabilities.

A lightweight MCP server that provides persistent knowledge graph storage for AI assistants, enabling memory across sessions through entity-relationship storage with JSON file persistence.

Enables AI tools to query context from a local JSON data source via stdio, demonstrating the Model Context Protocol.

A local MCP server that allows AI systems to search and retrieve information from a custom knowledge base generated from markdown files. It provides tools for natural language text search, category browsing, and specific content chunk retrieval.

Enables AI assistants to persistently add, read, and summarize sticky notes through MCP-compliant tools, resources, and prompts.