Google Gemini API Connects Generative Intelligence to Real World Actions via Function Calling

Google has released detailed documentation for its Gemini API function calling, a feature that allows artificial intelligence to act as a bridge to external systems. Instead of simply generating text, the model can now determine when to invoke specific tools and provide precise parameters to execute tasks. This capability marks a shift from passive chat to active agency, allowing the model to interact with databases and automate software workflows. The integration focuses on three primary goals: gathering knowledge from external bases, extending computational power, and taking direct actions. Users can prompt the model to schedule meetings, send emails, or even control smart home devices through structured API interactions. This infrastructure relies on function declarations that define a tool's purpose and required inputs using the OpenAPI schema standard.

Models in the Gemini 2.5 and 3 series introduce an internal thinking process to improve decision-making during these calls. This internal reasoning helps the AI better determine when a tool is necessary and how to handle complex, multi-turn conversations. To maintain context across these interactions, the API uses thought signatures that preserve the model's reasoning continuity between requests.

Efficiency is further enhanced by parallel and compositional calling, which allow the model to trigger multiple actions at once or chain them sequentially. A single user request can now result in several simultaneous function calls, such as retrieving inventory data from multiple sources. Sequentially, the model can use the output of one function, like a location check, as the input for a second function, like a weather forecast.

Google has also integrated support for the Model Context Protocol, an open standard that simplifies connecting AI applications to external data. Furthermore, Gemini 3 models can now process multimodal content in function responses, allowing the model to read files or analyze images returned by a tool. These technical updates suggest a future where AI operates as a unified interface for all digital services.