"A server for finding information and resources about Word DOCX files" matching MCP servers:

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

MCP server for the Oura Ring API v2, enabling natural language queries about sleep, readiness, activity, heart rate, and more.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

Redmine for AI agents (Claude Code, Cursor, Copilot): search and read issues, projects, members, versions, wiki, time entries and reference data; extract text from attachments (PDF, DOCX, XLSX, ZIP); analytics such as release risks, blocker chains and stale issues. 32 read-only tools by default, 7 optional write tools. Java, stdio, Docker image available.

An MCP server that demonstrates the Model Context Protocol using a mock SQLite database of an online store, offering tools for product search, sales analysis, and reviews, along with resources and prompts for learning MCP integration.

A CLI-based Model Context Protocol server that exposes PubNub SDK documentation and Functions resources to LLM-powered tools like Cursor IDE, enabling users to fetch documentation and interact with PubNub channels via natural language prompts.

A Model Context Protocol server that enables AI assistants to interact with MongoDB Atlas resources through natural language, supporting database operations and Atlas management functions.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.

Enables AI assistants to read, search, and traverse your entire reMarkable library, including handwritten notes via OCR.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.

Enables AI assistants to manage WordPress networks through a MainWP Dashboard, including site management, updates, plugin/theme control, and bulk operations via natural language.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

Enables AI assistants to scrape pages, batch-process URLs, and crawl entire websites with AI-powered extraction.

MCP server for AI-powered web research — search (Google, Brave, Serper, SearXNG), scrape any page, extract PDFs/DOCX/YouTube transcripts, academic & patent search. Single Go binary. Works with Claude, Cursor, Copilot, and any MCP client.

Enables local SOC 2 compliance work by scanning Infrastructure-as-Code, mapping findings to SOC 2 Trust Services Criteria, explaining risks in plain English, and drafting audit-ready documents without uploading files.

Enables Yelp business search, place details, and full review feeds as structured JSON through a hosted MCP endpoint, with no Yelp Fusion key required.

An MCP server for interacting with Reddit, enabling browsing, searching, content creation, and management with built-in safe mode and bot disclosure features.

mistral-mcp is a TypeScript MCP server (spec 2025-11-25) that exposes the full Mistral AI API surface: 22 tools: chat, OCR, audio (Voxtral), vision, agents, embeddings, moderation, classification, files, batch, sampling, FIM (Codestral), streaming 2 resources: mistral://models, mistral://voices 6 curated prompts (French + English) with MCP argument completion Dual transport: stdio (default) + Str