"A tool for searching and extracting relevant information from personal files" matching MCP servers:

Enables LLMs to access a user's personal writing context—voice, style, opinions, expertise, projects, and communication patterns—via curated markdown files, helping the LLM match the user's voice when generating written content.

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

A portable, AI-agnostic second brain that stores typed memories with semantic recall and self-learning re-ranking, exposed to any MCP-capable AI as a local server.

Stores and retrieves personal information fields securely, allowing Claude to access your name, address, email, and professional details without re-typing them.

A local MCP server that gives AI assistants a long-term memory by capturing sessions verbatim and surfacing relevant context automatically.

Auto-captures decision context from multi-agent workflows to preserve the 'why' behind every choice. Enables task traceability, reasoning retrieval, and continuous improvement across planning and implementation sessions.

Stores personal context as markdown files and exposes them via MCP for AI assistants to retrieve user preferences, skills, and background.

Enables querying, listing, and summarizing personal knowledge base documents using RAG with hybrid search and LLM.

Aggregates your digital footprint (GitHub, blogs, resume) into a single AI-readable profile and exposes it via MCP tools so AI agents can query your context live.

Provides a single-user, append-only, queryable memory store for dated facts with provenance, enabling Claude to persist and correct personal information across conversations via an MCP interface.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Provides a 'reflect' tool that creates cognitive checkpoints for AI assistants, forcing structured step-by-step reasoning through complex problems to improve accuracy and maintain context during task execution.

A PostgreSQL-backed MCP server for long-term personal memory, enabling context retrieval, memory saving, and read-only SQL queries for personal data.

A personal-life database with 47 tools across 13 domains, enabling semantic search and retrieval of memories, food, home, health, and more from any MCP-aware AI client.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Indexes local and enterprise documents to provide a unified personal knowledge base for AI clients via the Model Context Protocol. It supports full-text search across various file formats and integrates with platforms like Feishu and WeChat Work.

A modern MCP server that provides Claude Desktop with the ability to store and retrieve personal information locally.

MCP server that indexes your Obsidian notes into a Milvus vector database and enables querying them via a local or OpenAI LLM, with real-time synchronization.

A personal knowledge MCP server with vector database for the Opencode ecosystem. It enables semantic search, tag organization, and session memory logging, all running locally without external API keys.