strands-agents
A model-driven approach to building AI agents in just a few lines of code
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, low install friction, and a permissive Apache-2.0 license. It solves a real problem—reducing boilerplate for agent development—and its multi-provider abstraction makes it valuable for teams experimenting with different LLMs. Start with it if you're building agents in Python and want to avoid reinventing the agent loop.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10+.
- Default Bedrock provider requires AWS credentials and model access; other model providers have their own credential requirements.
- Low friction: pure Python wheel with no compiled dependencies.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and redistribution with minimal restrictions.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 6,904 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 36,172,755 downloads/mo, #735 on PyPI
Alternatives
Verify before relying
pip install strands-agents
from strands import Agent
agent = Agent()
agent("What is the square root of 1764")- Whether the 13 runtime dependencies (boto3, httpx, pydantic, jsonschema, etc.) introduce any transitive security concerns.
- Performance characteristics and latency profile for multi-agent systems at scale.
- Stability guarantees for the experimental bidirectional streaming feature and whether it affects production deployments.
- Availability and scope of pre-built tools accessible through MCP integration.
What it is and what it does
Strands Agents is a Python SDK that simplifies building AI agents by providing a model-driven abstraction layer. Instead of managing LLM API calls, tool definitions, and agent loops manually, you instantiate an Agent, pass it tools and a model provider, and call it like a function. The SDK handles prompt construction, tool invocation, and response streaming.
It abstracts away differences between model providers—Amazon Bedrock, OpenAI, Anthropic, Gemini, Ollama, LiteLLM, and others—so you can swap providers without rewriting agent logic. It natively supports Model Context Protocol (MCP) servers, which lets you attach pre-built tools without custom integrations. The package includes optional bidirectional streaming for real-time voice and audio conversations with supported models.
Use it for
- Build conversational assistants with tool access without managing LLM API details directly.
- Create multi-agent workflows where agents coordinate to solve complex tasks with different tool sets.
- Prototype and experiment with different LLM providers without changing agent code.
- Integrate MCP servers to give agents access to pre-built tools for domain-specific APIs.
- Deploy autonomous agents that watch for tool updates and adapt to new capabilities.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, low install friction, and a permissive Apache-2.0 license. It solves a real problem—reducing boilerplate for agent development—and its multi-provider abstraction makes it valuable for teams experimenting with different LLMs. Start with it if you're building agents in Python and want to avoid reinventing the agent loop.
Install
strands-agents on PyPI
Before you install
Low friction: pure Python wheel with no compiled dependencies. Active maintenance—released 2 days ago with 6904 GitHub stars. Supports Python 3.10 through 3.14.
Requires Python 3.10+. Default Bedrock provider requires AWS credentials and model access; other model providers have their own credential requirements.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and redistribution with minimal restrictions.
Quickstart
pip install strands-agents
from strands import Agent
agent = Agent()
agent("What is the square root of 1764")Verify before relying
- Whether the 13 runtime dependencies (boto3, httpx, pydantic, jsonschema, etc.) introduce any transitive security concerns.
- Performance characteristics and latency profile for multi-agent systems at scale.
- Stability guarantees for the experimental bidirectional streaming feature and whether it affects production deployments.
- Availability and scope of pre-built tools accessible through MCP integration.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 13 packagesboto3botocoredocstring-parserhttpxjsonschemamcpopentelemetry-apiopentelemetry-instrumentation-threadingopentelemetry-sdkpydanticpyyamltyping-extensionswatchdog |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 36,172,755 / month, #735 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python Modules |
Evidence: strands_agents-1.52.0-py3-none-any.whl
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See also strands-agents-builder · strands-agents-tools · stirrup · smolagents · praisonaiagents · strands-agents-evals · PraisonAI · mistralai-vibe-sdk · fast-agent-mcp · cua-agent