How to integrate Clarifai using MCP
Run models and manage AI applications and inputs. This guide creates an MCP server from Arthur's Clarifai template — tools preconfigured against https://api.clarifai.com — and finishes by sharing the server's MCP swagger documentation.
Steps
Open the Secrets vault and create a secret named
CLARIFAI_API_KEYholding your API key. Send Authorization: Key. Store the complete value including the Key prefix if the Arthur authentication configuration does not add it automatically. 


Go to the REST API Templates gallery and search for Clarifai.


Click Use template on the Clarifai card to open the server-creation dialog.


Review the server name and select
CLARIFAI_API_KEYin the credential field — the dialog only accepts vault secrets, and it lists every tool that will be created.


Click Create server. Arthur creates the server, applies the authentication, and generates all the tools.





Open the server's Tools tab to review the generated tools.

Open the server's Connect section and click Share the MCP swagger documentation — Arthur generates the public documentation link and QR code for this server.



Confirm it worked
The server appears with 2 preconfigured tool(s): predict_with_model, list_models. The Connect section offers the MCP swagger documentation — a shareable page with setup instructions for any AI client.
Good to know
- Invoke Clarifai models and inspect models in an application through the v2 REST API. Use a Personal Access Token for Clarifai-owned or cross-application resources, or an app-specific key for resources confined to that app.
- This integration requires a credential (api-key). Get one at https://clarifai.com/signup.
- Official API documentation: https://docs.clarifai.com/resources/api-overview/
- Editing a tool later never changes the template — templates are starting points, and the server is fully yours after creation.
Related
Tutorial video