agent-tool-routing

Dynamic tool routing is implemented by providing agents with frameworks to select tools based on task requirements, capabilities, and cost. You can use LLM-based, rule-based, or cost-optimized routing strategies to enable flexible decision-making.

Orchestrating tool selection in multi-agent systems requires intelligent frameworks that evaluate available external services. This approach provides selection mechanisms and tool execution logic with retry capabilities to handle complex interactions reliably.

Yes, MCP integration is fully supported to facilitate seamless connections with external services. It provides specific integration patterns for the Model Context Protocol to enable agents to interact with external resources effectively.

Agents decide between real-time APIs and cached data tools by evaluating current conditions and available resources. Cost-optimized routing strategies programmatically weigh task requirements against tool capabilities and execution costs to make the optimal selection.

Yes, you can use rule-based selection instead of LLM-based routing. The framework supports both approaches, allowing you to choose deterministic rules or LLM-based decisions depending on your need for predictability or contextual flexibility.

Tool execution handles failures using built-in retry logic during agent orchestration. This mechanism ensures that transient errors in external service interactions do not break the workflow, allowing the system to recover and complete tasks reliably.