MCP MongoDB Integration

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

A Model Context Protocol (MCP) server that provides AI coding assistants with specialized tools for analyzing and migrating Java applications from Java EE 8 (javax.*) to Jakarta EE 9+ (jakarta.*). T

基于Anduin2017 / HowToCook （程序员在家做饭指南）的mcp server，帮你推荐菜谱、规划膳食，解决“今天吃什么“的世纪难题； Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"

One API for Search, Crawling, and Sitemaps

A Serper MCP Server

The Milvus MCP server enables AI applications to interact with Milvus vector databases using natural language commands. It allows AI models to perform vector searches, manage collections, and retrieve data without writing custom database queries. This integration facilitates seamless access to vector data, enhancing the capabilities of AI tools like Claude Desktop and Cursor.

Transform your conversations into professional visualizations instantly. MockFlow IdeaBoard lets you create flowcharts, mindmaps, cloud architecture diagrams, charts, kanban boards, and more—just by describing what you need. What you can create: • Flowcharts & process diagrams • Mindmaps for brainstorming • AWS, Azure & GCP architecture diagrams • Charts (pie, bar, line, area, scatter, radar) • Data tables & spreadsheets with formulas • Interactive maps with location markers • Kanban boards for project tracking • Customer journey maps • Calendars with events • Whiteboards with sticky notes Every visualization is instantly shareable via URL and can be edited in MockFlow's visual editor. Perfect for developers documenting systems, product managers mapping user journeys, teams planning sprints, or anyone who thinks visually. No design skills needed—just describe your idea and get a polished diagram in seconds.

This server contains 5 tools. It could be used to simulate cascading failure scenario for lifeline network recovery (LNR). It has been tested in a case of Shelby County.

AI-powered image content safety detector using NSFWJS to classify potentially inappropriate content with fallback analysis, supporting GIF/Animated WebP/APNG and JPEG/PNG/WEBP.

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Official Firecrawl MCP Server - Adds powerful web scraping to Cursor, Claude and any other LLM clients.

MCP server to provide Figma layout information to AI coding agents like Cursor

SIGMAEO is a comprehensive SEO intelligence MCP server that provides 52 powerful tools for AI assistants like Claude and ChatGPT. Domain Intelligence: Analyze any website's traffic, authority metrics, keyword rankings, backlink profile, and identify top competitors. Keyword Research: Discover keyword opportunities with search volume, difficulty scores, CPC data, and topical clustering. Find content gaps between you and competitors. SERP Analysis: Get complete search results breakdowns including featured snippets, People Also Ask questions, and ranking factors for any keyword. Page Audits: Run comprehensive on-page SEO audits covering meta tags, headings, readability, E-E-A-T signals, and technical issues. Technical SEO: Check Core Web Vitals, crawl errors, internal linking structure, and site-wide technical health. Competitor Analysis: Compare multiple domains side-by-side, track ranking changes, and uncover competitor content strategies. AI Citation Tracking: Monitor your brand's presence in Google AI Overviews and responses from ChatGPT, Claude, Gemini, and Perplexity. Secure OAuth 2.0 authentication. Real-time data. Multi-region support for US, UK, AU, and more.

A Go implementation of the Model Context Protocol (MCP) server for Atlassian Confluence Data Center

GoalMochi isn’t a goal tracker—it’s a brand new way to manage your aspirations. Instead of juggling endless lists, GoalMochi guides you to focus on one goal at a time, forging a deeply personal narrative that keeps you motivated and on track. Powered by conversational AI, GoalMochi provides constructive insights and creative storytelling tailored to your unique motivations, helping you see your goal through to completion with a sense of momentum and fun. Goal Mochi works because it weaves proven visualization techniques into your planning process. Research shows that using mental imagery when forming implementation intentions leads to higher rates of goal achievement.¹ By collaborating with an AI “thought partner,” you’ll generate personally meaningful stories that tap into your intrinsic motivators, priming both your mind and emotions to move forward. It’s not about ticking boxes—it’s about intuitive goal management that meets you where you are and adapts with you. At the heart of this approach lies GoalMochi’s GoalMochi Agent, which transforms the typical, often dull process of goal tracking into an engaging, fun, and deeply resonant experience. With every completed goal, your insights and progress are securely captured, so you can reflect and build on them in the future. You don’t have to abandon your usual tools—track your tasks wherever you like. GoalMochi simply turns goal-tracking into a dynamic story that evolves, energizes, and empowers you to achieve what matters most. Getting started is EASY! 1. Email story@GoalMochi.com with some details about you and the goal you want to achieve 2. Log into GoalMochi.com with the same email address (or with a Google account connected to your email) to schedule a daily goal summary to be emailed to you 3. Email story@GoalMochi.com at any time to request a new story about your goal or give feedback, tell GoalMochi you've completed your goal and want to work on a new one, and so on. Stories from GoalMochi and daily summaries include AI deep research, so you're both inspired and informed!

A high-performance, pure Rust Model Context Protocol (MCP) server that provides persistent, semantic, and graph-based memory for AI agents. Unlike other memory solutions that require a complex stack (Python + Vector DB + Graph DB), this project is a single, self-contained executable. ✅ No External Database (SurrealDB is embedded) ✅ No Python Dependencies (Embedding models run via embedded ONNX runtime) ✅ No API Keys Required (All models run locally on CPU) ✅ Zero Setup (Just run one Docker container or binary) It combines: Vector Search (FastEmbed) for semantic similarity. Knowledge Graph (PetGraph) for entity relationships. Code Indexing for understanding your codebase. Hybrid Retrieval (Reciprocal Rank Fusion) for best results.

Python MCP server for Hevy fitness app. Log workouts with natural language, search exercises, manage routines. Features web interface, demo mode, and 22 MCP tools.

A Model Context Protocol (MCP) server that provides AI coding assistants with specialized tools for analyzing and migrating Java applications from Java EE 8 (javax.*) to Jakarta EE 9+ (jakarta.*). The Jakarta Migration MCP Server enables your AI coding assistant to: - Analyze Jakarta Readiness - Assess Java projects for migration readiness with detailed dependency analysis - Detect Blockers - Identify dependencies and code patterns that prevent Jakarta migration - Recommend Versions - Suggest Jakarta-compatible versions for existing dependencies - Create Migration Plans - Generate comprehensive, phased migration plans with risk assessment - Verify Runtime - Test migrated applications to ensure they run correctly after migration The Problem It Solves Migrating from Java EE 8 (javax.*) to Jakarta EE 9+ (jakarta.*) is complex because: - Dependency Hell: Many libraries haven't migrated, creating transitive conflicts - Binary Incompatibility: Compiled JARs may reference javax.* internally - Hidden Dependencies: javax.* usage in XML configs, annotations, and dynamic loading - Risk Assessment: Need to understand migration impact before starting This MCP server provides AI assistants with the specialized knowledge and tools to navigate these challenges effectively.

Web content fetching and conversion for efficient LLM usage