"Equipment or items used in windsurfing" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

Enables users to describe an LLM fine-tuning job and receive the cheapest, fastest, or most balanced GPU options across multiple cloud providers by calculating required VRAM and FLOPs.

It enables users to describe an LLM fine-tuning workload once and automatically estimates required VRAM/FLOPs, compares live GPU pricing across cloud providers, and returns ranked cheapest, fastest, or balanced hardware recommendations.

Enables users to describe an LLM fine-tuning workload and receive VRAM/FLOPs estimates plus ranked GPU recommendations across multiple cloud providers, optimizing for cost, speed, or balance.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

Aggregates multiple MCP services into a single unified interface with self-configuration capabilities, enabling dynamic addition and removal of tools via conversation.

Enables any MCP client to drive the user's real Chrome profile through a Chrome extension bridge, with tools for navigation, accessibility snapshots, ref-based interactions, console/network reading, screenshots, tab management, and restricted script evaluation.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.

Enables users to describe an LLM fine-tuning job and receive ranked GPU recommendations across a dozen cloud providers based on estimated VRAM/FLOPs, live pricing, cost, and speed. It returns cheapest, fastest, and balanced hardware options without manual comparison.

Enables users to describe an LLM fine-tuning job once and get ranked GPU hardware recommendations with estimated VRAM/FLOPs, cost, and runtime across a dozen cloud providers.

It enables users to describe an LLM fine-tuning workload once and receive ranked GPU recommendations for cheapest, fastest, or balanced options across many cloud providers by estimating VRAM/FLOPs and aggregating live pricing.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Enables users to describe an LLM fine-tuning workload and receive ranked, task-aware GPU recommendations by estimating required VRAM/FLOPs and comparing live pricing across a dozen cloud providers.

Enables users to describe an LLM fine-tuning job once and receive ranked GPU recommendations across many cloud providers based on estimated VRAM/FLOPs, cost, and runtime.

Enables users to describe a fine-tuning workload and receive ranked GPU cloud recommendations based on required VRAM/FLOPs, cost, and runtime across multiple providers.

Enables users to describe an LLM fine-tuning workload once and receive ranked cloud GPU recommendations with estimated VRAM/FLOPs requirements, cost, runtime, and data-source transparency.

Enables users to describe an LLM fine-tuning workload once and get task-aware VRAM/FLOPs calculations with cheapest, fastest, and balanced GPU recommendations across a dozen cloud providers. It supports CLI, REST API, and natural-language MCP integration without manual price comparison.

Enables users to describe an LLM fine-tuning workload and automatically estimate VRAM/FLOPs to recommend the cheapest, fastest, and balanced GPU options across multiple cloud providers. It supports natural-language requests through MCP, returning structured ranked hardware recommendations without manual price comparison.

Enables sharing coding progress on Twitter by analyzing sessions and generating tweet suggestions, with tools for posting tweets, threads, and OAuth authentication.

Unifies Roblox Studio, Unity, Unreal Engine, and Blender into a single AI-powered control plane with 78 tools for automated game development.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

This MCP server enables MCP Apps-compatible hosts to render an interactive React-based UI and invoke a sample tool over streamable HTTP or stdio transports.

Enables a bot to inspect, query, create, edit, and script Roblox Studio instances in token-cheap batches, plus run Luau, playtests, screenshots, and inputs through Roblox's official Studio MCP connection. It runs locally over stdio or an authenticated local HTTP endpoint, returning small structured answers instead of dumping whole games into context.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

Blocks AI coding assistants from installing non-existent packages and accessing non-existent files.

A task-level STDIO MCP server that lets Codex or any other MCP client hand off scoped coding jobs to an asynchronous worker agent which reads the code, edits files, and runs tests, while the client keeps ownership of planning and acceptance. Exposes submit, wait, query, follow-up, and cancel tools so multiple clients can queue and monitor tasks against a chosen project root.

A versatile MCP server providing tools for arithmetic operations, n8n webhook integration, and access to a customer support playbook resource. It also includes specialized prompt templates for converting webinar transcripts into engaging blog posts.

Enables mobile device automation for Android (via ADB) and iOS Simulator (via simctl), allowing you to control devices with natural language through screenshots, UI interactions, text input, and app management.

A TypeScript-based MCP server that enables AI assistants to create, search, list, and delete notes with tags. Serves as a starter template for building custom MCP servers with tools and resources.

LLM-assisted, safety-gated Postgres migrations exposed as an MCP server, using a deterministic rule engine over Postgres's own parser AST for safety enforcement, with two-phase approval and append-only audit ledger.

MCP server for remote debugging of Apps in Toss mini-apps, providing CDP relay and test runner capabilities.

A comprehensive collection of 103 tools providing capabilities for text processing, data analysis, web development, and business management in a single server. It is designed for rapid deployment to Vercel and integrates seamlessly with MCP clients like Claude and Cursor to automate diverse workflows.

MCP server: is this GitHub repo still maintained? A verdict.

Enables users to describe an LLM fine-tuning job in natural language so the server estimates required VRAM/FLOPs and searches live GPU pricing across a dozen cloud providers. Returns ranked cheapest, fastest, and balanced hardware recommendations with each result's data source clearly identified.

Enables Claude Code to drive your everyday logged-in browser session — opening and closing tabs, navigating, clicking, typing, scrolling, filling forms, uploading files, taking screenshots, and reading page text, console output and network requests. It runs through a local native-messaging bridge, scoping each client session to its own window behind yours.

Enables clients to interact with a spec-shaped Model Context Protocol endpoint over Streamable HTTP, supporting initialization, session handling, tool listing and calls, plus ping, with origin validation and protocol version enforcement.