This weblog submit focuses on new options and enhancements. For a complete checklist, together with bug fixes, please see the launch notes.
We’re rolling out two key options that change the way you construct AI utilizing Clarifai: help for AI brokers and the Mannequin Context Protocol (MCP).
AI Brokers: Constructing Smarter, Autonomous AI
AI brokers are a giant step past single-task AI fashions. As an alternative of simply doing one factor, an agent can cause, plan, and take a number of actions to realize a bigger objective. Consider them as AI applications that may break down advanced issues and use completely different instruments or fashions to get the job performed.
With this launch, we’re making it simpler to construct these brokers on Clarifai. This implies you possibly can:
- Create goal-oriented AI: Design programs that work in the direction of particular targets, not simply offering remoted solutions.
- Chain collectively AI capabilities: Mix a number of fashions and instruments on our platform (or exterior ones) in sequence to unravel extra advanced issues.
- Automate multi-step processes: Cut back guide effort by having AI deal with complete workflows.
This opens up potentialities for extra superior AI purposes that may make selections and adapt to conditions.
To indicate you what and how one can construct AI Brokers, we have created an AI Weblog Writing Agent utilizing Clarifai and CrewAI!
On this video, we construct an AI-powered weblog writing agent that generates full weblog posts from scratch. We use:
- CrewAI to handle agent orchestration
- Gemini 2.5 Professional mannequin powered by Clarifai
- Streamlit to create a easy and interactive UI
MCP: Giving AI Brokers Actual-World Context
For AI brokers to be actually helpful, they want entry to real-time info from outdoors their inner knowledge. The Mannequin Context Protocol (MCP) solves this by offering a standardized approach for AI fashions and brokers to work together with exterior knowledge sources and APIs.
We have built-in MCP, permitting you to:
- Join brokers to your knowledge: Bridge your AI brokers along with your firm’s databases, knowledge lakes, and different inner programs.
- Entry dwell knowledge: Give your brokers present info from exterior APIs, like monetary knowledge, information, or sensor readings.
- Construct customized knowledge bridges: Create your individual MCP servers to tailor how your AI brokers entry and use exterior context.
Combining AI brokers with MCP means your AI can’t solely suppose and plan but in addition actively fetch and use real-world info, making your AI purposes extra highly effective and related. Be taught extra right here.
Clarifai now presents an OpenAI-compatible API endpoint, permitting you to make use of your current OpenAI code and workflows to run inferences with Clarifai fashions, together with those who combine or wrap OpenAI fashions.
The compatibility layer robotically interprets OpenAI-style requests into Clarifai API calls, so you possibly can entry Clarifai’s broad mannequin library as customized instruments inside your OpenAI-based tasks.
This removes the necessity to rewrite your code for Clarifai’s native API, making integration quick and easy for groups already accustomed to OpenAI.
Under is an instance that makes use of the OpenAI Python consumer library to work together with a Clarifai mannequin by way of Clarifai’s OpenAI-compatible API endpoint. Learn extra right here
We now have made quite a few enhancements to the Python SDK to boost stability, usability, and integration capabilities:
We’re excited in regards to the new Agentic and MCP help in Clarifai and are trying ahead to seeing the sorts of purposes the group builds round it. Try our video tutorial on constructing an AI Weblog Writing Agent to see AI Brokers in motion. You can too discover extra examples right here.
Discover the documentation and begin constructing at the moment. We’ll even be including extra agent examples and templates quickly, so keep tuned.
When you’ve got any questions, ship us a message on our Neighborhood Discord channel. Thanks for studying!
