Replicate for model hosting
Replicate runs hosted models behind a simple API, and for model hosting its official server is our second pick. It is strong when you want to invoke open-source models for inference without standing up or paying for your own GPUs, which is exactly the case where running a model should be a single request rather than an infrastructure project.
It sits behind Hugging Face here because Hugging Face is the model hub teams reach for first when the job is discovery and a registry. Replicate's edge is on the run side: the agent finds a hosted model and calls it, and the inference happens on Replicate's hardware.
How Replicate fits
The catalog tools let an agent locate a model: search_models ranks public models by relevance, list_models paginates the full set, get_models returns metadata for a specific owner and name, and get_models_readme plus list_models_examples show how to call it. Inference runs through create_models_predictions against an official model with the inputs you supply. For teams managing their own models, create_models and delete_models register and remove them, and list_hardware reports the CPU and GPU SKUs available for runs and trainings.
The honest limits: this is hosted inference, so it does not run models on your own machine the way Ollama does, and it is not a full training-and-registry platform the way Hugging Face is. Baseten fits better when you need dedicated, tuned production endpoints with autoscaling control, and Ollama fits better when the model must stay local and private. Reach for Replicate when you want to call open-source models on demand without owning the GPUs, and rank it first only if hosted inference breadth is your single priority over a registry.
Tools you would use
| Tool | What it does |
|---|---|
| get_account | Return information about the user or organization associated with the provided API token. |
| list_collections | List the collections of models featured on Replicate, as a paginated list of collection objects. |
| get_collections | Get a single collection of models by slug, including the nested list of models in that collection. |
| list_hardware | List the available hardware SKUs (CPU and GPU types) for running models and trainings. |
| search_models | Get a list of public models matching a search query, ranked by relevance. |
| list_models | Get a paginated list of public models on Replicate. |
| get_models | Get the metadata for a public model by owner and name. |
| create_models | Create a new model on Replicate under your account or organization. |
| delete_models | Delete a model you own. The model must have no versions and no predictions. |
| get_models_readme | Get the README content (Markdown) for a model. |
FAQ
- Does Replicate's MCP server run models locally?
- No. Replicate is hosted inference, so create_models_predictions runs the model on Replicate's hardware, not your machine. If the model must stay local and private, Ollama is the better fit; Replicate ranks second here precisely because its strength is running models without owning GPUs.
- Can the agent register its own models on Replicate?
- Yes. create_models adds a model under your account or organization and delete_models removes one that has no versions or predictions. For full model-hub and registry workflows, though, Hugging Face is the stronger pick, which is why it ranks ahead of Replicate for model hosting.