Can AI call multiple tools at once?
Parallel vs. sequential calls
Some models support parallel tool calling, where they can request multiple tool calls simultaneously. This is useful when the calls are independent, such as fetching weather for two cities at once.
Other models or configurations may only support sequential calls, where the model calls one tool, gets the result, then decides on the next call. This is more common in older or simpler implementations.
The ability to call multiple tools depends on the model and the API. For example, OpenAI's function calling supports parallel calls in some models, while others may not.
- Check the model's documentation for parallel tool calling support.
- Design your application to handle multiple tool calls in one response.
- Ensure tools are idempotent if called in parallel.
- Consider rate limits and resource usage when allowing parallel calls.
- Test with your specific model to confirm behavior.
Handling multiple tool calls
When the model returns multiple tool calls, your application must execute them and return the results in the correct order. The model then uses these results to formulate a final answer.
If calls are dependent, the model may need to wait for one result before making the next call. This is handled through multiple rounds of interaction.
In MCP, the client can manage multiple tool invocations, but the protocol itself doesn't dictate parallel execution; it's up to the implementation.
Common mistakes
- Assuming all models support parallel tool calling; it varies.
- Not handling multiple tool calls correctly, leading to errors or missed results.
- Overloading the system with too many parallel calls, causing timeouts.