Verified project record

strands-agents/harness-sdk

A model-driven framework for building AI agents in code with built-in context management, execution limits, and observability. It requires configuring external model provider credentials and is designed for developers writing Python or TypeScript.

Project overview

Project type: MCP · AI Agent
Use cases: Coding & Development · Automation
Deployment: Refer to project documentation
License: Apache-2.0

Best for

Developers and AI engineers who write code to build and manage production-grade AI agents across various cloud and model providers.

Key capabilities

A model-driven agent loop that traces every decision by default.
First-class support for Amazon Bedrock, Anthropic, OpenAI, and Gemini, plus custom ones.
Hooks to intercept any step to log it, validate it, or redirect it, allowing agents to correct themselves.
Provides reusable tools like a calculator for agents.
Mechanisms to catch mistakes before they run.
Built-in support for multi-agent systems and structured output.
Built-in MCP support.
Built-in bidirectional streaming.

Limitations and risks

Requires configuring model access and credentials for a provider.
Requires Python 3.10+.
Requires Node.js 20+.

Getting started

Install the framework using simple pip or npm install commands, then run the 3-line Agent example to verify functionality.

Evidence and sources

GitHub project description: Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.
README: Build an agent harness. Control it end-to-end.
README: This monorepo contains the Python SDK, TypeScript SDK, documentation site, and supporting packages:
README: Stay in control. The agent loop traces every decision by default. Hooks let you intercept any step to log it, validate it, or redirect it.
README: Model agnostic. First-class support for Amazon Bedrock, Anthropic, OpenAI, and Gemini, plus many more providers and custom ones.

Reviewed at: 2026-07-15T15:29:55Z