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ToolProduction ReadyMCP
sdk-python
by strands-agents
Model-driven Python SDK for building observable multi-agent systems
Python
Updated Feb 11, 2026
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Summary
Provides a model-driven Python SDK to build and run AI agents with minimal code. Uses declarative agent definitions and pluggable model backends to wire up multi-agent flows, tool use, and observability. Includes integrations for common LLM providers and telemetry hooks for tracing agent interactions.
Key Benefits
As agents coordinate and delegate, understanding their behavior and provenance becomes essential for trust. trust and provenance visibility help teams move from ad-hoc scripts to reproducible agent pipelines suitable for tracking agent track record and failure modes.
Target Use Cases
Teams prototyping or deploying multi-agent applications who need rapid agent composition with telemetry and multi-backend LLM support.
Applications
- Compose specialized agents and delegate subtasks with declarative agent definitions
- Instrument agent interactions for tracing and telemetry to debug failure modes
- Swap model backends (openai, anthropic, llama, bedrock, ollama) while keeping the same agent logic
Works With
openaianthropicbedrockllamaollamalitellmopentelemetry
Topics
agenticagentic-aiagentsaianthropicautonomous-agentsbedrockgenailitellmllama+9 more
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Keywords
multi-agent orchestrationmulti-agent trustagent-evaluation