"Understanding local computer vision models like YOLO" matching MCP servers:

Enables searching, comparing, and inspecting AI models by pricing, context window, and capabilities via the models.dev catalog.

Classifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

MCP server that lists available GitHub Models and compares responses from multiple models for the same prompt.

An MCP server that wraps the @apitomy/data-models library for querying, validating, and editing OpenAPI and AsyncAPI documents.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

An MCP server that helps interact with and compare different GitHub Models, enabling listing, filtering, and comparing model responses.

An MCP server for computer automation that provides tools for screenshots, mouse actions, keyboard input, and drag-and-drop functionality. It supports cross-platform desktop interaction for both Linux (X11) and Windows environments.

Gives text-only LLM coding agents vision by routing images to a multimodal model and returning detailed textual descriptions. Supports local files, URLs, clipboard, base64, raw bytes, and multiple providers like OpenAI, Anthropic, and Gemini.

Provides native macOS computer control tools including mouse and keyboard simulation, screenshot capture, and application management for MCP-compatible agents. It enables AI assistants to directly interact with the macOS operating system and installed apps through standard tool calls.

A local development MCP server that exposes MySQL databases to VSCode and Copilot CLI with read-only SELECT queries and INSERT/UPDATE operations. It provides secure, schema-specific database access for development environments only.

Enables MCP clients to scan local GGUF models, estimate VRAM and suggest GPU offload layers, manage llama-server lifecycle, and proxy OpenAI-format chats with idle auto-unload.

Enables blind AI coding models to debug visual bugs by capturing screenshots, analyzing them with a vision-capable model, and returning a written report.

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

A local vision-language MCP server that enables Claude Code to perform image analysis, OCR, and UI-to-code generation using the Qwen3 VL 4B model via LM Studio. It provides privacy-focused visual processing by running entirely on the user's local hardware without external API dependencies.

A local STDIO server that exposes OpenProject API v3 as MCP tools, allowing MCP clients like Codex CLI and GitHub Copilot CLI to reference projects and work packages.

Wraps local multimodal CLIs (Google Gemini CLI and Qwen CLI) as MCP tools, enabling text-only AI assistants like Claude to analyze images through relay calls. Supports local paths, URLs, and base64 image inputs with configurable models and output formats.

A high-performance, cross-platform MCP server for split-screen window management on Windows and macOS, providing 16 window manipulation tools.

A remote MCP server on Cloudflare Workers that lets text-only development agents analyze webpage, error, and annotated screenshots via SenseNova 6.7 Flash-Lite through a single tool. It supports local dev, Cloudflare deployment, and integration with clients like Claude Code and Pi.

Local-first memory daemon for AI coding agents that captures session transcripts, distills typed memories (decisions, facts, lessons, commands, todos), and serves them via hybrid search through MCP tools.