Open-source Together AI MCP alternatives
The community Together AI server is open source and narrowly scoped: it generates images with FLUX.1 Schnell through a single generate_image tool. Because it is open, you can read exactly how it calls the API and which key it uses before adding it. Every alternative below publishes its source too.
Reading the repo is the angle here, which matters for AI servers that send prompts and content to a model provider. The picks span image tools, audio and translation, and model platforms, each noted by what its open source lets you verify.
The 8 best open-source alternatives
The community Gemini server is open source and generates text, analyzes images, counts tokens, and creates embeddings. The code shows exactly which Gemini API calls an agent can make before you connect it.
Set up Google Gemini →Open and built for editing, the Stability AI community server goes beyond generating to upscale, outpaint, and restyle images with Stable Diffusion. Reading the repo confirms which image operations it performs.
Set up Stability AI →fal.ai's open-source server generates and edits images, video, music, and audio with 600+ models. Given that breadth, having the source to audit which models and operations it exposes is worthwhile.
Set up fal.ai →- BasetenOfficial
Baseten's open-source servers give an agent live access to your model deployments and docs to deploy, call, and operate models. The source lets you verify how it reaches your deployments.
Set up Baseten → - DeepLOfficial
DeepL's official server is open source and does machine translation, document translation, and AI rephrasing across 30+ languages. You can audit exactly what text it sends for translation.
Set up DeepL → - ElevenLabsOfficial
ElevenLabs' official server is open and covers text-to-speech, voice cloning, speech-to-text, sound effects, and conversational AI. For a tool that handles voice data, reading the source before connecting is sensible.
Set up ElevenLabs → - Hugging FaceOfficial
A discovery layer over the open ecosystem, the Hugging Face official server is open source and searches and explores models, datasets, Spaces, papers, and docs, with code you can inspect.
Set up Hugging Face → - LangfuseOfficial
To observe and audit model calls, the open-source Langfuse server manages prompts, queries traces and observations, runs evals, and inspects LLM metrics. Useful alongside a generation server.
Set up Langfuse →
How to choose
Every server here ships its code, so the difference is the modality, not auditability. For image work, Stability AI and fal.ai go beyond Together's single model; Gemini adds text and image analysis. ElevenLabs covers audio and DeepL covers translation. Baseten and Hugging Face are model platforms, and Langfuse observes the calls the others make. Read the repo before granting an AI server access to your prompts and content, especially for media it sends to a provider.
FAQ
- Is the Together AI MCP server open source?
- Yes. The community Together server is open source, so you can read how it calls the image API and which key it uses. It is scoped to image generation with FLUX.1 Schnell. Every alternative on this page is open source as well.
- Why choose an open-source AI MCP server?
- You can verify which model calls and data the server sends to a provider, pin or patch the version you run, and keep API keys on infrastructure you control. For servers that transmit prompts, images, or voice, that visibility lowers the surprise of an unexpected request.