"A system for managing personal knowledge and organizing information" matching MCP servers:

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.

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.

Captures AI-assisted work into a searchable ledger and exposes it via MCP for querying past conversations and decisions.

Provides current weather information for any location and generates AI-powered responses using Google Gemini through FastMCP.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

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 Personal Knowledge-Base MCP Server that provides semantic search over a student-owned document collection using MCP, Gemini embeddings, and Qdrant. It exposes tools for searching notes, retrieving full documents, and listing indexed sources.

Personal local AI memory/document MCP that manages short and long-term memories and Markdown documents, with tools for import, search, and retrieval.

Enables semantic search over a personal document corpus through MCP tools, allowing users to retrieve ranked chunks, access full document context, and list sources from their semester notes.

Provides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.

Enables users to audit personal reading streams by quantifying category diversity with Shannon entropy, detecting lexical redundancy and echo chambers via Jaccard similarity, and ranking content sources by decibel signal-to-noise ratio for pruning recommendations.

Enables local zero-knowledge encryption of a personal vault and sanitization of PII such as credentials, credit cards, and addresses before dispatch to cloud LLMs, with client-side rehydration of masked data.

This MCP server enables users to analyze personal reading and media streams by computing Shannon entropy, detecting Jaccard redundancy and echo chambers, and ranking content sources by decibel SNR to produce pruning recommendations and high-signal curation.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Enables agents to compile a personal knowledge vault into a linked graph by indexing bi-directional links and parsing [[wikilinks]], tags, and unlinked mentions across notes. It runs deterministically over MCP without external dependencies, turning raw note collections into navigable, queryable knowledge structures.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

A local-first RAG system that indexes personal documents and enables querying them via an MCP tool, keeping data private with local embeddings.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables agents to compile a personal knowledge vault into a graph with bi-directional link indexing by parsing [[wikilinks]], tags, and unlinked mentions across notes. Runs as a zero-dependency MCP server, so MCP clients can build and query note connections deterministically without LLM round-trips.

Enables grounded, dated research from a curated AI-knowledge repository, offering free BM25 retrieval and a research loop that combines the knowledge base, curated sources, and the open web with tiered citations.

A secure, read-only MCP server for AI-powered system monitoring. It provides real-time OS metrics, config discovery, and safe log tailing to enable autonomous infrastructure audits without shell access risks.

Enables Claude to monitor CPU, memory, disk, processes, network connections, Docker containers, and system logs for system diagnostics and troubleshooting.

Provides system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.

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.

A self-hosted, MIT-licensed MCP server that securely connects private documents and markdown files to LLMs. It provides a lightweight, local-first RAG infrastructure compatible with any MCP-enabled AI client or framework.

Local knowledge engine for codebases with hybrid search, knowledge graph, and interaction tracking, enabling Claude Code to search and interact with project knowledge locally.

A Model Context Protocol server that exposes an airline design system as a queryable knowledge base, enabling AI to discover components, find components for use cases, and scaffold prototypes.

Lets an AI assistant search, read, and write notes and sources in your self-hosted Open Notebook, with approval-gated writes and no data sent anywhere else. It bundles tools, prompts, and skills for meeting notes, decision records, weekly reviews, and source-cited research.

A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.