"How to check differences between files" matching MCP servers:

Enables structural framing analysis of documents, identifying perspectives, omissions, and reader positioning, with numerical claim verification against authoritative sources.

Enables LibreChat agents to manage per-user private files, persistent documentation, RAG indexing and semantic search, and publish files via secure opaque public links.

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.

Enables an AI agent to verify its draft answer against supplied sources sentence by sentence, flagging unsupported figures, dates, citations, and must/may wording and offering source-backed corrections. An optional judge mode can additionally assess prose via a configured LLM endpoint, while default operation is deterministic and offline.

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.

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.

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.

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

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

A Model Control Protocol server that integrates with Claude Desktop to enable simultaneous querying and cross-checking of responses from multiple LLM providers including OpenAI, Anthropic, Perplexity AI, and Google Gemini.

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.

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.

Exposes any SQLite database as read-only MCP tools for AI assistants, enabling listing tables, describing schemas, and running SELECT queries with filtering, ordering, and pagination.

MCP server for Google's Gemini File Search (RAG). Manage file search stores, upload documents, and query with RAG through 12 tools.

A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.

Google Chat MCP server that lets AI assistants like Claude and Cursor participate directly in team conversations - search messages, help teammates, share files, and coordinate across chat platforms.

A Model Context Protocol server that helps users migrate subscription businesses from RevenueCat to Adapty through natural language interactions with LLMs like Claude Desktop.

Enables local-first knowledge management for Codex, providing tools for guided discussions, contextual recall, review, and daily topics.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

Crawl entire websites, sitemaps, and documentation portals into clean, LLM-ready Markdown without ads, cookie popups, or noise for RAG pipelines and AI agents.

Enables travel-related queries and planning including weather, train and flight information, itinerary generation, and travel knowledge retrieval via RAG, using an AI agent with MCP protocol.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables persistent session memory for LLMs by trust-scoring and injecting verified context between conversations.

Enables seamless integration between Ollama's local LLM models and MCP-compatible applications, supporting model management and chat interactions.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

A server that enables LLMs like Claude to interact with Azure Cosmos DB databases through natural language queries, acting as a translator between AI assistants and database systems.

This server enables interaction between Neo4j databases and Claude Desktop, allowing users to execute Cypher queries, create nodes, and establish relationships in the database.

Advanced content gap analysis using Query Decomposition and Keyword Fan-Out (Google's patented methodology). Tells you exactly what user queries your content covers - and what it misses. Built on academic research because I needed to understand how AI search engines actually evaluate content.

A multi-API key load balancing MCP server for Tavily that automatically rotates between multiple API keys to provide high availability and increased request limits.

Arbor is a local-first, high-performance developer tool designed to bridge the gap between static code analysis and AI-driven development.

A Model Context Protocol server that reduces token consumption by efficiently caching data between language model interactions, automatically storing and retrieving information to minimize redundant token usage.

A proxy server that sits between MCP clients and servers, providing authentication, tool discovery, caching, and guardrail enforcement to protect MCP servers from malicious inputs.

Enables AI coding agents to index local codebases and search them by natural-language intent, find related files through imports and semantic similarity, and check indexing status. All processing runs locally via MCP tools.

The Wanaku MCP Router stands between autonomous AI agents and your enterprise systems. Wanaku leverages proven integration technology, like Apache Camel, to set up and manage hundreds or thousands of integrations.

A server enabling seamless interaction between AI models and WordPress sites with secure, standardized communication using the WordPress REST API for comprehensive site management.

Routes each coding task to the best-fitting spec-driven-development framework with explainable rules, then enforces deterministic lifecycle gate checks between phases so progress can't skip required artifacts or evidence. Assembles per-phase context packs from a company knowledge base with app-scoped memory and cross-app lookup, while the host agent remains the only actor that edits files or runs tests.