"A system or tool for enabling computer vision capabilities in an MCP (Microcontroller Platform)" matching MCP servers:

An open-source MCP server that lets any coding agent operate your computer like a person does—reading the UI through accessibility trees, clicking and typing in the background, showing an agent pointer, zooming into regions, and driving your signed-in Chrome on macOS, Windows, and Linux.

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 AI agents to use a desktop computer with event-driven settling, waiting for the screen to react and stabilize before returning a settled screenshot and verdict.

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug

Open-source MCP vision server that gives text-only LLMs and AI agents image understanding: OCR, visual inspection, annotation reading, UI layout analysis, screenshot-to-code reconstruction, and image comparison, with Ollama, OpenAI-compatible, Anthropic, or Gemini backends.

Open-source computer use MCP server for macOS and Windows, including remote Windows over SSH. Reads accessibility/UI Automation trees and uses Jev for element selection and action verification, with optional screenshot localization for icons and game scenes.

Enables Windows desktop automation via MCP, allowing AI agents to control mouse, keyboard, and screen capture with the same interface as Anthropic's computer-use tool.

Search 47,000+ marketing agencies and get AI-matched with fitted agencies, from Pick an Agency.

MCP server for the Mamba Labs Ecommerce Platform Profiler actor on Apify. Detect the ecommerce platform, payment providers and catalogue size behind a storefront.

Local OCR & image analysis via Apple Vision Framework — private, offline, no API keys. Extracts text from images and PDFs, detects faces, barcodes, QR codes, and document corners. Works with Claude Code, Claude Desktop, and Cursor.

An MCP server that adds vision capability to any LLM by forwarding images to OpenRouter vision models, returning text analysis. Supports image analysis, model listing, and config diagnostics.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables AI agents to read Excel files with full content extraction, including embedded images, cell data, formulas, and merged cells, returning multimodal content for vision-capable models.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Enables coding agents to ask what a window shows and receive a concise JSON answer from a local Ollama model instead of ingesting the full accessibility tree, reducing token usage. It is read-only and supports optional session context, health checks, and model release.

MCP server for Azure resource management, AI Foundry, and Entra ID — inspect and operate Azure infrastructure through AI agents.

Enables AI agents to interact with ServiceNow through MCP, providing schema inspection, record CRUD, attachments, audit, Flow Designer, and platform investigations with policy-guarded access.

Server that enables AI assistants to interact with Storybook design systems. Extract component HTML, analyze styles, and help with design system adoption and refactoring.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

Fully local AI assistant that watches your screen (OCR, accessibility text, window titles) and exposes that context via an MCP server, with local RAG via Ollama. No cloud, no data leakage.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

MCP server for describing video, image, audio, and text using the Gemini 3.1 Flash Live API with persistent WebSocket sessions.

Enables self-hosted AI gateway and agent control plane with governed MCP tools, virtual-key budgets, caching, and audit, supporting OpenAI, Anthropic, Gemini, MCP, and A2A protocols. It provides deterministic prompt enhancement and governed execution with a zero-credential first run.

Enables agents to control Windows desktop applications through UI Automation and Win32, supporting window management, mouse/keyboard input, element inspection, screenshots, OCR, macro recording, and autonomous multi-app missions. It also provides an HTTP/stdio MCP interface, an operator UI, and optional telemetry and safety controls.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

MCP server that detects and guards against tool poisoning and prompt injection attacks in tool descriptions and schemas. It provides risk scoring, pattern detection, safe rewriting, and audit reports with zero external API cost.