"A server for Linux file operations" matching MCP servers:

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

A multi-agent operations assistant that answers business questions by searching local documents and order records.

An MCP server exposing internal business operations as tools — task management (create, list, update status) and RAG-style semantic search over an internal knowledge base (leave, expense, and onboarding policies) that any MCP-compatible AI agent can call directly for grounded, non-hallucinated answers.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

A proof of concept MCP server for Apache OFBiz

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Provides tools for searching and reading local files, supporting metadata filters, PDF full-text keyword search, and sandboxed file access.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables semantic search over personal files using natural language, with optional AI summarization, all running locally.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

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.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

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.

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.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

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

Turns any static website into an MCP-searchable knowledge base by deploying a Cloudflare Worker that provides full-text search tools, enabling AI assistants to search and retrieve content from your site.

A Model Context Protocol server that enables large language models to interact directly with Couchbase databases through natural language, supporting operations like querying buckets, performing CRUD operations, and executing N1QL queries.

An integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.