"Running MySQL Queries Through a MySQL Socket" matching MCP servers:

Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

Provides access to developer roadmap content from roadmap.sh, allowing users to list available roadmaps and fetch detailed Markdown content for specific career paths.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables AI assistants to interact with OpenAPI documents for analysis, validation, and management through structured interfaces.

MCP server that enables introspection of any MCP server's registered tools by exposing mcpreg/list, mcpreg/get, and mcpreg/query tools, making tool registry accessible even when the underlying SDK lacks list_tools().

Enables interaction with Siemens Polarion requirements management system through natural language. Supports authentication, project management, work item queries, document access, and requirements analysis.

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.

Provides AI agents with access to a comprehensive database of 200+ Next.js documentation URLs for intelligent document selection and retrieval. Enables Claude and other AI assistants to analyze user queries and recommend the most relevant Next.js documentation pages.

Enables AI assistants to query and retrieve a structured professional profile, including expertise areas, CV, projects, active research, and target AI queries, through dedicated MCP tools and resources.

An MCP server for KG Financial's payment services integration, enabling AI coding tools to generate accurate code by automatically searching payment integration documentation through natural language queries.

Enables AI assistants to access Ramp's developer documentation and API schemas through natural language queries. Provides contextual answers about API endpoints, authentication methods, data relationships, and implementation patterns for developers building on Ramp's platform.

Enables users to search and access DOOR support documentation and knowledge base articles through natural language queries. Provides fast search capabilities across support.door.com content including articles and PDFs with pre-built search indexing.

A unified MCP server for Glyphs font design software, integrating handbook queries and API reference lookups. Enables searching documentation, managing plugins, and accessing development templates through Claude.

This server allows users to interact with their Zotero library through the Model Context Protocol, providing tools for searching items, retrieving metadata, and accessing full text using natural language queries.

Provides comprehensive contextual information about npm packages including README files, versions, dependencies, download statistics, and search functionality. Enables users to explore and analyze npm packages through natural language queries with intelligent GitHub README fetching and branch fallback.

Enables LLMs to search and retrieve PayNow Component documentation directly, accelerating system integration through natural language queries.