# Knowledge Management

MCP integration service for Confluence and Jira

A RAG service based on the Qdrant vector database and Ollama/OpenAI embedding, providing document semantic search and management functions.

This project provides a set of tools for crawling website content and generating Markdown documents. It also implements semantic search for documents through the MCP server and supports integration with tools such as Cursor.

MCP Obsidian is a model context protocol server designed for the Obsidian note library, enabling integration with MCP clients such as Claude Desktop and supporting note search, reading, and writing functions.

MemoDB MCP is a TypeScript - based AI conversation and knowledge management server that provides functions for user management, conversation data storage, and knowledge base operations.

The Logseq MCP Server is a model context protocol server that provides direct integration with Logseq knowledge bases, enabling LLMs to interact programmatically with Logseq graphs.

This extension integrates the Basic Memory knowledge base system into the Zed Editor's assistant function, enabling the construction of a persistent knowledge base through natural conversations and storing it as Markdown files on a local MCP server.

The DeepLucid3D UCPF Server is an MCP service based on the Unified Cognitive Processing Framework, providing tools for advanced cognitive analysis, creative problem-solving, and structured thinking.

The Anytype MCP server is a model context protocol service based on the Anytype API, allowing AI assistants and other MCP clients to interact with Anytype data, including functions such as querying, creating, and deleting spaces and objects.

This project is a GitHub repository for testing and exploring the implementation of the Model Context Protocol (MCP) server, containing sub - projects related to learning multiple programming languages, DevOps tools, game development, and AI.

The RAG Document MCP Server is a vector search-based document processing tool that provides document retrieval and context enhancement functions for AI assistants.

A document semantic search service based on the Qdrant vector database, supporting URL and local file imports and providing natural language query functions.

An MCP service for document retrieval based on vector search, providing relevant document context for AI assistants to enhance their answering ability

Basic Memory is a tool for building persistent knowledge through natural conversations with large language models (LLMs). It stores data locally in Markdown files and implements the MCP protocol for two - way knowledge management.

Memex is a tool based on the Model Context Protocol (MCP) for analyzing web page content and adding it to a knowledge base, supporting Q&A interactions via the Claude API.

An Obsidian plugin that provides local MCP server capabilities, enabling external applications to interact with the Obsidian library through standardized interfaces, including file operations, semantic search, etc.

Implementation of the Kibela MCP server to enable LLMs to interact with Kibela content

A server project based on FastMCP that provides the function of searching the Obsidian note library through a REST API interface.

Logseq MCP toolset that provides local Logseq interaction capabilities for AI agents

The Claudesidian MCP Server is a service project that interacts with the Obsidian knowledge base. It provides functions such as note management, web scraping, and memory retrieval, and supports local deployment and extended development.

An MCP server for document retrieval and processing based on vector search, providing document enhancement functions for AI assistants

This project provides a series of MCP servers and dedicated AI agents to extend Claude's capabilities, including package management, knowledge graphs, reasoning engines, and integration capabilities with multiple platforms.

MCP Atlassian is an integrated tool that provides Model Context Protocol services for Atlassian products (Confluence and Jira). It supports cloud and server/data - center deployments and can implement functions such as content search, page management, and issue tracking.

An MCP service for document retrieval based on vector search, providing relevant document context to enhance the response ability of AI assistants

A Python server project based on the MCP protocol, which uses OpenAI's vector storage function to build a RAG system, supporting the creation of vector databases from multiple file formats and semantic search.

An MCP server for interacting with the Logseq personal knowledge management system through custom instructions, providing note retrieval and to-do item management functions

Obsidian's MCP Tools plugin provides AI applications with the ability to securely access the knowledge base

The SourceSync.ai MCP Server is a standardized implementation of a knowledge management platform interface that allows AI models to interact with the SourceSync.ai platform through the MCP protocol.

This analysis report summarizes the most interesting MCP (Model Context Protocol) servers discussed on the X platform on March 19, 2025, focusing on their practicality in AI - driven workflows. Through discussions and blog posts on the X platform, the report identifies the most popular and recommended MCP servers, including Reddit, Notion, Google Sheets, Gmail, and Discord, which are favored for their automation capabilities and ease of use. In addition, servers with specific functions such as SendAI Kit and Dolphin - MCP, as well as pre - built servers provided by Anthropic, are also mentioned.

A server based on the Model Context Protocol for interacting with Rememberizer's document and knowledge management API, enabling large - language models to search, retrieve, manage documents, and integrate.