"A server for finding information and resources about Arduino" matching MCP servers:

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

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

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 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 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.

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.

Medicare claim documentation lookup for CPT codes against live CMS sources, returning structured requirements and document URIs with optional enrichment via RCI APIs.

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

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.

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.

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 AI assistants to search and retrieve documentation, component specs, theme guides, and CLI commands for the Meta Astryx Design System, providing structured tools and guidelines for coding agents.

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

Enables IDEs like Cursor, Windsurf, and Claude Code to access and query Appwrite documentation through a vector-powered search system. Provides developers with contextual Appwrite documentation directly within their development environment.

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.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

A read-only MCP server providing curated Qdrant documentation for LLMs, enabling retrieval of the latest and most accurate documentation.

MCP server for Wiki.js with full GraphQL API coverage, fine-grained permissions, multi-user support, and deployable on Vercel.

Serves read-only tools that let an agent inspect PDFs step by step: outline a document, search for text or figure values, read pages and tables in order, describe figures and chart data, and render page or block images, with every block cited to its page and bounding box. It also lists the PDFs available under a configured root folder, which it never reads outside of.

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.

This MCP server enables reading and analyzing various file formats, including PDF, DOCX, XLSX, and CSV, by extracting metadata, searching for keywords, and reading structured content. It also provides capabilities to create new documents and convert files between supported formats.

Pulls up-to-date, version-specific documentation and code examples for libraries directly into your prompt, preventing outdated or hallucinated APIs.

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

Enables scraping and searching documentation websites using semantic or keyword search, with support for multiple deployment modes.

An MCP server that retrieves and cleans official documentation for popular AI/Python libraries via web search and LLM processing, exposing a get_docs tool.