Open-source Baseten MCP alternatives
Baseten's servers are open source, even though you reach the model-deployment and docs tools as hosted endpoints. So the audit story already starts well. The reason to look further is usually that you want a different kind of model server, or one you can run locally as well as read.
Every option below publishes its code. Most run inference for a specific media type; one tracks LLM behaviour rather than serving models. Several install locally, so you can both read the repo and keep the process on your own machine.
The 8 best open-source alternatives
Fully open source, this community Gemini server runs the model: generate text, analyze images, count tokens, and create embeddings. You can read exactly which API calls it makes before pointing it at your key.
Set up Google Gemini →The Stability AI community server is open source and generates, edits, upscales, outpaints, and restyles images with Stable Diffusion. Small enough to review before granting it your credentials.
Set up Stability AI →Open and broad, the fal.ai community server covers images, video, music, and audio across 600-plus fast models, with tools like generate_image and inpaint_image. The repo shows the full set it can call.
Set up fal.ai →A single open-source tool, generate_image on the FLUX.1 Schnell model, is the whole of this community Together AI server. Easy to audit end to end given how narrow its surface is.
Set up Together AI →- DeepLOfficial
DeepL's official server is open source and translates text and documents across 30-plus languages, with rephrasing and glossary tools. It runs locally, so you can read the code and keep the process yours.
Set up DeepL → - ElevenLabsOfficial
ElevenLabs' official server is open source and does text-to-speech, voice cloning, speech-to-text, sound effects, and conversational agents. Audit the repo before wiring voice generation into your workflow.
Set up ElevenLabs → - Hugging FaceOfficial
Hugging Face's official server is open source and searches models, datasets, Spaces, papers, and docs. The discovery counterpart to Baseten's reference side, with code you can read in full.
Set up Hugging Face → - LangfuseOfficial
Open source and built for LLM tracing, the official Langfuse server manages prompts, queries traces and observations, runs evals, and inspects metrics. Adjacent to model serving: it watches behaviour rather than running inference.
Set up Langfuse →
How to choose
Every option here is open source, so all of them can be audited before you connect them. For running model inference you can also keep local, Gemini, Stability, fal.ai, ElevenLabs, and DeepL all ship code and install on your machine. Hugging Face covers discovery, and Langfuse watches LLM behaviour rather than serving models. Read the repo before granting any of them an API key.
FAQ
- Is the Baseten MCP server open source?
- Yes. Baseten publishes the code for its servers, even though you reach the model-deployment and docs tools as hosted endpoints. You can read what they do without running them yourself. Every alternative on this page is open source too.
- Which open-source alternative can I run locally?
- Gemini, Stability, fal.ai, Together, DeepL, and ElevenLabs all install locally over stdio, so the server process and its credentials stay on your own machine. Hugging Face and Langfuse publish their code as well but are reached as hosted endpoints.