🚀 The Future of AI Development is Here

Write your AI agents once in Python. Use them everywhere, from any programming language, with zero infrastructure complexity.

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The Problem Every AI Developer Faces

You’ve built an incredible AI agent in Python. It uses LangGraph for complex reasoning, leverages powerful tools, and produces amazing results. Your team loves it. Then reality hits: Your frontend team needs it in JavaScript, your mobile team wants it in Kotlin, your Unity team wants it in good old C#, your systems team requires it in Rust. The traditional approach? Build separate implementations, REST APIs, WebSocket handlers… Sound exhausting? That’s because it is.

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What RunAgent Actually Does

RunAgent fundamentally changes how AI agents work. Here’s the magic: Hero Light Hero Dark Your Python function signatures automatically become API contracts for every supported language: 
def analyze_market(company: str, timeframe: str = "1year") -> dict:
    return langgraph_agent.invoke({"company": company, "timeframe": timeframe})
The Revolutionary Insight: Change your Python function signature, and all language SDKs automatically adapt. No API versioning, no breaking changes.

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Getting started

The fastest way to experience the magic is with RunAgent:
  1. Install the CLI (includes Python SDK): 
    pip install runagent
  2. Create your first agent: 
    runagent init my_agent
  3. Deploy locally: 
    runagent serve my_agent
…and you’re ready to access your Python agent from any supported language.

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Multi-Language SDK Support

RunAgent provides native-like access to your deployed agents across multiple languages:

Python SDK

Native async/sync support with streaming capabilities. Access your agents like local functions.

JavaScript SDK

Full TypeScript support with streaming and Promise-based APIs for modern web applications.

Rust SDK

High-performance async SDK with futures and streaming support for systems programming.

Go SDK

Idiomatic Go client with goroutines and channel-based streaming (coming soon).

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Framework Support

RunAgent works with any Python-based AI agent framework:

LangGraph

Deploy your LangGraph agents with built-in state management and workflow execution.

LangChain

Turn your LangChain agents into production-ready APIs with automatic scaling.

CrewAI

Deploy multi-agent CrewAI systems with coordinated execution and monitoring.

AutoGen

Deploy Microsoft AutoGen multi-agent conversations with step-by-step execution.

AG2

Deploy AG2 conversational agents with fact-checking and multi-turn interactions.

Agno

Deploy Agno AI agents with print response capabilities and streaming support.

LlamaIndex

Deploy LlamaIndex agents with RAG capabilities and mathematical tools.

Letta

Deploy Letta memory-enabled agents with persistent conversations and tool integration.

OpenAI

Deploy native OpenAI API agents with completion and streaming capabilities.

Custom Framework

Use any Python-based framework by defining simple entrypoint functions.

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Real-Time Streaming Across Languages

When your Python agent streams responses, RunAgent makes it feel native in every target language: 
def generate_report(topic: str) -> Iterator[str]:
    yield f"# {topic} Analysis Report\n\n"
    yield "## Executive Summary\n"
    for section in analyze_topic(topic):
        yield f"### {section.title}\n{section.content}\n\n"
What’s happening: WebSocket connections, real-time data flow, and native iteration patterns—all handled automatically by RunAgent.

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