"Proof-of-concept examples for Multi-Component Processes (MCPs)" matching MCP servers:

This MCP server enables image analysis through a single tool that supports multiple vision models and API providers, with automatic failover and persistent state management.

Provides vision capabilities to Reasonix, enabling analysis of images/videos, OCR, and comparisons via OpenAI-compatible vision models.

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

Enables AI agents to interact with NexusAPI's asynchronous generation API, including model discovery, schema inspection, task creation, and status retrieval.

Bridges DeepSeek (text-only) with vision models via MCP, enabling image description and compression using any OpenAI-compatible visual API.

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 AI agents and MCP-compliant clients to extract visual data from charts and graphs into structured markdown tables using deterministic, zero-dependency Python.

A server that allows AI tools like Claude and Cursor to automate and control Photoshop through natural language commands, enabling tasks like editing PSDs, toggling layers, and generating marketing creatives.

Provides tools to fetch IIIF manifests and retrieve specific image regions or scaled images for analysis. This server enables detailed interaction with International Image Interoperability Framework resources, supporting tasks like image description and transcription.

Provides various utilities including timezone-aware time queries, basic calculator operations, multilingual greetings, code review prompts, and AI image generation through Hugging Face API.

Provides comprehensive functionality including weather data, system utilities, Azure cloud management, and AI-powered image generation and editing. Features interactive parameter selection through MCP elicitation for enhanced user experience.

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

A FastMCP server implementation that provides a standardized interface for accessing AI models hosted on Replicate's API, currently supporting image generation with customizable parameters.

A template MCP server that provides job searching tools (analyze descriptions, fetch postings, search opportunities) and basic image processing capabilities. Includes built-in authentication and is designed to work seamlessly with Puch AI.

Provides job search capabilities including analyzing job descriptions, fetching job postings from URLs, and searching opportunities, plus basic image processing tools like converting images to black and white.

Enables AI-assisted image generation from text prompts using multiple providers (Tencent Hunyuan, OpenAI DALL-E 3, and Doubao) with support for various artistic styles, resolutions, and negative prompts through a unified interface.

Runs a Model Context Protocol server directly on Axis cameras, enabling any MCP-capable AI to inspect and control the camera without cloud or middleware.

Enables AI agents to inspect and drive Blender scenes directly, either through a live editor bridge on port 8190 or automatically via headless background CLI when Blender is closed. Provides token-efficient tools for scene outlining, object creation and modification, modifiers, materials, rendering, asset export, and arbitrary bpy script execution.

A multimodal meal planning agent that uses Gemini Vision to analyze fridge photos, suggest recipes, provide nutritional info, and generate daily meal plans.

Generates blog and social media images using Google's Gemini AI with pre-configured platform presets for Ghost, Medium, Instagram, Twitter, LinkedIn, YouTube, and more.