"A server for connecting to databases using MCP" matching MCP servers:

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Converts any OpenAPI/Swagger spec into an MCP server, exposing REST API endpoints as tools for Claude.

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Enables local conversion of PDFs to Markdown, with automatic OCR fallback for scanned pages, image extraction, and page-by-page structure preservation.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

Provides Large Language Models with real-time access to the latest documentation for Python libraries like Langchain, LlamaIndex, and OpenAI, enabling accurate and up-to-date code suggestions.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Provides AI assistants with locally bundled tools to explore NIST OSCAL models, retrieve schemas, list community resources, and generate valid OSCAL templates for governance, risk, and compliance workflows.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Converts Markdown files to Atlassian Document Format and publishes them to Confluence, with support for rendering Mermaid diagrams as PNG attachments.

Enables converting Markdown text into clean HTML for headings, lists, code blocks, tables, links, and images, with optional full-document wrapping via x402 micropayments.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

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.