"Parsing and Unparsing CSV Files for AI Context Use" matching MCP servers:

A self-hosted MCP server that enables AI agents to see and control a Windows PC through screenshots, built-in Arabic/English OCR, mouse, keyboard, clipboard, and application launching, with code-enforced consent and audit logging.

Enables an agent to process local video files and then read, search and inspect the results: timestamped transcripts, on-screen text and key frames as images. Everything runs locally, so an agent can answer questions like how to perform a task shown in a screencast or meeting recording.

Local MCP server for Gateway-managed computer use that exposes computer.* tools with desktop control, OCR, and user-visible safety overlays.

Enables Codex to submit, poll, and retrieve bounded text handoffs for durable image-generation and image-inspection jobs while keeping provider-returned media bytes outside the MCP boundary.

Enables context-bounded image generation and inspection through durable local jobs, returning only bounded text handoffs, hashes, relative references, and Job IDs while keeping provider media bytes off the public MCP boundary.

Enables persisted image generation and inspection jobs through bounded MCP tools, returning only compact text handoffs, hashes, relative references, and Job IDs while keeping provider-returned media outside public results.

Enables Codex to run image generation and inspection as durable, restart-reconcilable local jobs that keep provider-returned media behind the tool boundary and hand back only bounded text, hashes, relative references, and Job IDs. It also supports idempotent submission, job history, and an offline deterministic mock provider for validating transport and persistence behavior without spending API credits.

Give your AI assistant eyes and ears — analyze any video, audio, or image, entirely on your machine.

MCP server that gives AI chat real vision by reading images, files, logs, and zip archives via local OCR in any language, with privacy-first processing.

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-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.

A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.

Enables MCP clients to discover OpenRouter image and video models, generate and edit images, create variations, launch and monitor video jobs, and save resulting media into authorized local project directories with cost controls.

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

A customizable Model Context Protocol server implementation that enables AI models to interact with external tools including weather queries, Google search, and camera control functionality.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Enables Codex to run durable, context-bounded image generation and inspection jobs through local MCP tools, returning compact text results, hashes, relative references, and Job IDs instead of media bytes.

Enables text-only coding models to read images, PDFs, presentations, spreadsheets, and other non-text files through a single analyze_media tool, combining local document extraction, OCR, and optional vision models with clear evidence labeling.

Enables Codex to run context-bounded image generation and inspection as durable local jobs, returning bounded text handoffs, hashes, relative references, and Job IDs while keeping provider-returned media bytes outside the MCP boundary.

A durable local MCP server that runs image generation and inspection as persisted jobs, keeping provider-returned media bytes behind the MCP boundary while returning only bounded text handoffs, hashes, relative references, and Job IDs. This keeps image-heavy Codex workflows context-bounded, idempotent, and resumable, with offline mock or optional OpenAI providers.