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stirrup

The lightweight foundation for building agents

Worth itPyPI Python ModulesReleased Aug 2026241.1K downloads / mopermissive licensePure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — stirrup-0.2.0-py3-none-any.whl
v0.2.0 · released 2026-08-04 · Python >=3.12 · 11 runtime deps: anyio, filetype, httpx, json-schema-to-pydantic, moviepy, openai, pillow, pydantic

Yes. Stirrup is actively maintained, has low install friction, carries a permissive MIT License, and addresses a real need for a lightweight, unopinionated agent framework. Its 548 GitHub stars and recent activity suggest community traction. No known security vulnerabilities. Best suited for developers building agents who want flexibility over rigid frameworks.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.12 or later.
  • API key environment variable (OPENROUTER_API_KEY or equivalent for your provider) must be set before running.
  • Low friction installation with a pure Python wheel.

License · maintenance · safety

permissive license (permissive) — MIT License permits unrestricted use, modification, and redistribution with minimal restrictions, making it suitable for both commercial and open-source projects.

last release 2026-08-04 (10 days) · last repo commit 2026-08-05 · 548 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 241,087 downloads/mo, #8,888 on PyPI

Verify before relying

pip install stirrup

import asyncio
from stirrup import Agent
from stirrup.clients.chat_completions_client import ChatCompletionsClient

async def main():
    client = ChatCompletionsClient(
        base_url="https://openrouter.ai/api/v1",
        model="anthropic/claude-opus-5",
        max_tokens=8_192,
        context_window_tokens=1_000_000,
    )
    agent = Agent(client=client, name="agent", max_turns=15)
    async with agent.session(output_dir="./output") as session:
        finish_params, history, metadata = await session.run("Your task here")

asyncio.run(main())
  • Whether all 11 runtime dependencies are required for core functionality or only for optional features like video processing or web search
  • Performance characteristics and latency when running agents with many tool calls or long conversation histories
  • Compatibility scope with LLM providers beyond OpenAI-compatible APIs and LiteLLM
Same gist for agents: .md · .json

What it is and what it does

Stirrup is a lightweight agent framework designed to work with language models rather than impose rigid workflows on them. It provides a foundation for building autonomous agents that can execute code (locally, in Docker, or E2B sandboxes), search and fetch web content, call external tools via MCP servers, process files, and incorporate human feedback. The framework includes built-in context management to handle long conversations, multimodal support for images and video, and a flexible tool system based on Pydantic schemas.

The package ships with sensible defaults—local code execution and web search tools—but is fully customizable. You can use it as an installed package or fork it as a template for building specialized agents. It supports multiple LLM providers through OpenAI-compatible APIs, LiteLLM, or custom clients, and includes a skills system for modular, domain-specific instruction packages. The 11 runtime dependencies cover HTTP requests, image and video processing, schema validation, and retry logic.

Use it for

  • Build an autonomous research agent that searches the web, fetches articles, and synthesizes findings into a report
  • Create a code-generation agent that writes, tests, and refines scripts based on user requirements
  • Develop a data analysis agent that processes files, executes analysis code, and generates visualizations
  • Set up a multi-tool agent that integrates with external services via MCP to automate complex workflows
  • Prototype a specialized agent by cloning the repository and customizing the core loop and tool set

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

Stirrup is actively maintained, has low install friction, carries a permissive MIT License, and addresses a real need for a lightweight, unopinionated agent framework. Its 548 GitHub stars and recent activity suggest community traction. No known security vulnerabilities. Best suited for developers building agents who want flexibility over rigid frameworks.

Install

stirrup on PyPI

Before you install

Low friction installation with a pure Python wheel. Active maintenance—last commit 2026-08-05, released 2026-08-04—and 548 repository stars suggest ongoing development. Requires Python 3.12 or later.

Requires Python 3.12 or later. API key environment variable (OPENROUTER_API_KEY or equivalent for your provider) must be set before running.

License in practice

MIT License permits unrestricted use, modification, and redistribution with minimal restrictions, making it suitable for both commercial and open-source projects.

Quickstart

pip install stirrup

import asyncio
from stirrup import Agent
from stirrup.clients.chat_completions_client import ChatCompletionsClient

async def main():
    client = ChatCompletionsClient(
        base_url="https://openrouter.ai/api/v1",
        model="anthropic/claude-opus-5",
        max_tokens=8_192,
        context_window_tokens=1_000_000,
    )
    agent = Agent(client=client, name="agent", max_turns=15)
    async with agent.session(output_dir="./output") as session:
        finish_params, history, metadata = await session.run("Your task here")

asyncio.run(main())

Verify before relying

  • Whether all 11 runtime dependencies are required for core functionality or only for optional features like video processing or web search
  • Performance characteristics and latency when running agents with many tool calls or long conversation histories
  • Compatibility scope with LLM providers beyond OpenAI-compatible APIs and LiteLLM

Package facts

Licensepermissive license permissive
Python supportSupports the current Python release >=3.12
Install frictionLow. Pure-Python wheel
Runtime dependencies
11 packages
anyiofiletypehttpxjson-schema-to-pydanticmoviepyopenaipillowpydanticrichtenacitytrafilatura
MaintenanceActively maintained 10 days since the last release
Last repo commit
First released
Downloads241,087 / month, #8,888 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: MacOSOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python ModulesTyping :: Typed

Evidence: stirrup-0.2.0-py3-none-any.whl

Tags

Capabilities
llm agent frameworkai agent buildercode execution agentautonomous agent frameworktool-calling agent librarymulti-tool agent systemlightweight agent framework
Topics
agent-frameworkllm-toolsasync-first
PyPI keywords
aiagentllmopenaianthropictoolsframework

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See also ai-parrot · strands-agents · fast-agent-mcp · langchain · npmai-agents · smolagents · PraisonAI · openai-agents · livekit-plugins-anthropic · deepagents

Further reading