"How to create .docx documents for Microsoft Word" matching MCP servers:

Enables AI agents to query Microsoft Entra data using natural language, converting requests into Microsoft Graph API calls for read-only enterprise IT scenarios.

Enables interactive chat with AI models, including document retrieval and command-based prompts via the Model Control Protocol.

Search a folder of documents and check answers against them. Offline: no API key or database.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

An MCP server that enables searching Merill's Weekly Microsoft AI Roundup archive with natural language queries, returning sourced excerpts, issue details, and tool mentions. It supports hybrid semantic and keyword search, issue retrieval, and archive browsing with no API keys required.

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.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

This read-only MCP Server allows you to connect to Microsoft Dataverse data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

This read-only MCP Server allows you to connect to Microsoft Excel data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out our MCP Server for Microsoft Excel (https://www.cdata.com/drivers/excel/download/mcp).

This read-only MCP Server allows you to connect to Microsoft Planner data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

MCP server that ingests PDF documents into pgvector for semantic search and RAG pipelines. It handles extraction, chunking, local embeddings, and storage, enabling agents to make PDFs searchable via natural language.

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 AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Enables Claude Desktop and other AI tools to interact directly with Figma, allowing for powerful AI-assisted design capabilities through natural language commands.

A proof of concept MCP server for Apache OFBiz

A lab demonstrating how to deploy a Model Context Protocol (MCP) server and integrate it with Microsoft Copilot Studio, allowing users to connect AI models to different data sources and tools through a standardized protocol.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.

MCP server enabling natural-language querying of SQLite databases via schema discovery, GraphRAG retrieval, and safely guarded read-only SQL execution.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

Enables users to create and control portable, user-owned memory archives, including saving memories, reflections, values, and stories, exporting them as open JSON, publishing or discovering public archives, and loading consented material as a clearly-labelled memory-based AI persona.

Enables AI clients to search a local literature library via vector semantic retrieval, with automatic conversion of Zotero items and arbitrary files into Markdown (including OCR for scanned PDFs). It supports natural language queries and provides answers with page-level citations.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

Enables any agent to query the same interview corpus as the UI over stdio, exposing tools to list transcripts, search quoted lines, retrieve verified themes with citations and dropped reasons, and fetch source lines.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

Enables users to audit websites and online stores for generative and answer-engine readiness, generate deployable llms.txt and llms-full.txt files, JSON-LD schema, and AI crawler rules, analyze robots access for AI bots, and extract clean page content for LLM use.