Flux Image Generation MCP Server

The Together MCP server is a dedicated image‑generation service that exposes the Flux.1 Schnell model through the Model Context Protocol. It addresses a common pain point for developers building AI‑powered applications: accessing high‑quality, controllable image generation without managing the underlying model infrastructure. By running as a stand‑alone MCP server, it can be discovered and invoked by any client that understands the MCP specification, enabling seamless integration into diverse workflows such as content creation tools, design assistants, or creative chatbots.

At its core, the server offers a single, well‑documented tool named . A developer simply supplies a text prompt and, optionally, parameters like dimensions, sampling steps, or the number of images to produce. The server validates these inputs against defined ranges and forwards the request to Together AI’s hosted Flux model, returning either a base64‑encoded image or a public URL. This abstraction eliminates the need for clients to handle API keys, model selection, or image post‑processing, allowing developers to focus on higher‑level logic.

Key capabilities include:

• High‑resolution output with adjustable width and height up to 2048 × 2048 pixels, suitable for print or web use.
• Fine‑tuned control over generation steps and image count, giving power users the ability to trade speed for detail.
• Flexible response formats that let clients choose between embedded base64 data or lightweight URLs, optimizing for bandwidth or storage constraints.
• Optional persistence by specifying an , enabling the server to write PNG files directly to disk, which is handy for batch processing pipelines or archival systems.
• Robust error handling that validates prompts and API responses, providing clear diagnostics for developers.

Typical use cases span from generating concept art for game assets to creating custom illustrations in a collaborative design platform. In a chatbot scenario, an assistant can ask the user for a prompt and immediately receive an image that is displayed inline or stored in a shared workspace. In a content‑management system, the server can be triggered during a publishing workflow to produce featured images automatically.

Because it follows MCP conventions, the Together server plugs into existing AI toolchains without modification. Clients can discover the tool, construct requests with standard JSON schemas, and handle responses uniformly. This plug‑and‑play nature makes it an attractive choice for teams that want to augment their applications with state‑of‑the‑art image generation while keeping infrastructure complexity minimal.