"How to connect to SQL Server" matching MCP servers:

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Hosted MCP server for structured knowledge extraction and entity enrichment, allowing users to author JSON schemas, enrich entities using multiple LLM providers, and benchmark model performance.

Enables AI agents to search, explore data lineage, understand business context, and generate SQL queries across an organization's data ecosystem.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

An MCP server that allows AI assistants to search and retrieve human-curated content recommendations from Copus.

Provides persistent, decay-aware memory for AI applications by integrating the Smara Memory API through semantic search and Ebbinghaus forgetting curves. It enables tools to store, search, and manage long-term user context with importance-based ranking and automatic decay.

Generic MCP server exposing Nexusm core capabilities (memory, conversation, knowledge, feedback, context) to MCP clients via stdio and Streamable HTTP transports.

An open-source server implementing the Model Context Protocol (MCP) that enables capturing insights from AI sessions and transforming them into persistent, searchable knowledge accessible across tools.

A Python MCP server that gives LLMs persistent, searchable access to project context — documentation, architecture decisions, and session notes.

MCP server for flomo that enables AI tools to quickly add notes to your flomo account via the API.

Provides access to the HUMMBL Base120 framework of 120 validated mental models organized across 6 transformations, enabling users to search, retrieve, and get AI-recommended mental models for problem-solving and decision-making.

A Model Context Protocol (MCP) server that provides AI assistants with secure access to Obsidian vaults. Enables reading, writing, searching, and managing notes without requiring Obsidian to be running.

An MCP server enabling LLMs to access WeChat Reading bookshelf, notes, highlights, and reviews via tools like get_bookshelf, search_books, and get_book_notes_and_highlights.

An MCP server that connects Limitless Pendant wearable data to AI tools like Claude and Windsurf, allowing AI assistants to interact with your personal Lifelog recordings through structured tools and searches.

MCP server for managing personal items with expiration dates, enabling AI agents to add, query, and scan barcode items via API Key authentication.

A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.

A lightweight bridge server that connects WeChat Reading (WeRead) data with Claude Desktop, allowing seamless access to reading notes and book collections through natural language interactions.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.

A Model Context Protocol server that enables Claude to persistently store, search, and manage text memories with tags in a local JSON file.