Runagent
RunAgent simplifies serverless deployment of your AI agents. With a powerful CLI, multi-language SDK support, built-in agent invocation & streaming suppprt.
Install / Use
/learn @runagent-dev/RunagentREADME
<div align="center"> <h3>🎉 News</h3> <h2>Introducing OpenClaw, PicoClaw, and ZeroClaw</h2> <p> <img src="./docs/logo/openclaw-white.jpg" alt="OpenClaw" height="56"/> <img src="./docs/logo/picoclaw.png" alt="PicoClaw" height="56"/> <img src="./docs/logo/zeroclaw.png" alt="ZeroClaw" height="56"/> </p> </div>
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[2026.03] 🚀 [Architecture] Introducing OpenClaw, PicoClaw (Go), and ZeroClaw (Rust): one unified engine that runs agents both serverless and as 24/7 always-on services.
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[2026.03] 🌍 [Milestone] The first architecture to support persistent + serverless agent execution in the same engine, with a single codebase powering both modes.
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[2025.12] 🎯 [New Product] Published RunAgent Pulse – Scheduling & Orchestration, a self-hosted “Google Calendar for your AI agents”.
What is RunAgent-Pulse?
RunAgent Pulse is a Google Calendar for Your AI Agents
A lightweight, self-hosted scheduling service designed for AI agents and developers.
Schedule agent executions with second-level precision, natural language scheduling, and seamless integration with RunAgent Serverless.
We’ve unveiled this as a companion project:
- GitHub: RunAgent-Pulse
Use it together with this repo to deploy agents (RunAgent) in our serverless cloud and then orchestrate/schedule them (Pulse).
What is RunAgent?
RunAgent is an agentic ecosystem that enables developers to build AI agents once in Python using any python agentic frameworks like LangGraph, CrewAI, Letta, LlamaIndex, then access them natively from any programming language. The platform features stateful self-learning capabilities with RunAgent Memory (coming soon), allowing agents to retain context and improve it's action memory over time.
RunAgent has multi-language SDK support for seamless integration across TypeScript, JavaScript, Go, and other languages, eliminating the need to rewrite agents for different tech stacks. RunAgent Cloud provides automated deployment with serverless auto-scaling, comprehensive agent security, and real-time monitoring capabilities.
Quick Start
Installation
pip install runagent
Initialize Your First Agent
# The basic
runagent init my-agent # Basic template
# Also you can choose from various frameworks
runagent init my-agent --langgraph # LangGraph template
runagent init my-agent --crewai # CrewAI template
runagent init my-agent --letta # Letta template
Agent Configuration
Every RunAgent project requires a runagent.config.json file that defines your agent's structure and capabilities.
This configuration file specifies basic metadata (name, framework, version), defines entrypoints for either Python functions or external webhooks, and sets environment variables like API keys. The entrypoints array is the core component, allowing you to expose functions from any Python framework (LangGraph, CrewAI, OpenAI) or integrate external services (N8N, Zapier) through a unified interface accessible from any programming language.
Example Configuration
{
"agent_name": "LangGraph Problem Solver",
"description": "Multi-step problem analysis and solution validation agent",
"framework": "langgraph",
"version": "1.0.0",
"agent_architecture": {
"entrypoints": [
{
"file": "agent.py",
"module": "solve_problem",
"tag": "solve_problem"
},
{
"file": "agent.py",
"module": "solve_problem_stream",
"tag": "solve_problem_stream"
}
]
},
"env_vars": {
"OPENAI_API_KEY": "your-api-key"
}
}
Local Development
Deploy and test your agents locally with full debugging capabilities before deploying to RunAgent Cloud.
Deploy Agent Locally
cd my-agent
runagent serve .
This starts a local FastAPI server with:
- Auto-allocated ports to avoid conflicts
- Real-time debugging and logging
- WebSocket support for streaming
- Built-in API documentation at
/docs
Deploy to RunAgent Cloud
Once your agent is tested locally, deploy to production:
# Authenticate (first time only)
runagent setup --api-key <your-api-key>
# Deploy to cloud
runagent deploy --folder .
Your agent will be live globally with automatic scaling, monitoring, and enterprise security. View all your agents and execution metrics in the dashboard.
LangGraph Problem Solver Agent (An Example)
# agent.py
from langgraph.graph import StateGraph
from typing import TypedDict, List
class ProblemState(TypedDict):
query: str
num_solutions: int
constraints: List[dict]
solutions: List[str]
validated: bool
def analyze_problem(state):
# Problem analysis logic
return {"solutions": [...]}
def validate_solutions(state):
# Validation logic
return {"validated": True}
# Build the graph
workflow = StateGraph(ProblemState)
workflow.add_node("analyze", analyze_problem)
workflow.add_node("validate", validate_solutions)
workflow.add_edge("analyze", "validate")
workflow.set_entry_point("analyze")
app = workflow.compile()
def solve_problem(query, num_solutions, constraints):
result = app.invoke({
"query": query,
"num_solutions": num_solutions,
"constraints": constraints
})
return result
async def solve_problem_stream(query, num_solutions, constraints):
async for event in app.astream({
"query": query,
"num_solutions": num_solutions,
"constraints": constraints
}):
yield event
🌐 Access from any language:
RunAgent offers multi-language SDKs : Rust, TypeScript, JavaScript, Go, Dart, C#/.NET, and beyond—so you can integrate seamlessly without ever rewriting your agents for different stacks.
<table> <tr> <td width="16.66%"><b>Python SDK</b></td> <td width="16.66%"><b>JavaScript SDK</b></td> <td width="16.66%"><b>Rust SDK</b></td> <td width="16.66%"><b>Go SDK</b></td> <td width="16.66%"><b>Dart SDK</b></td> <td width="16.66%"><b>C# SDK</b></td> </tr> <tr> <td valign="top">from runagent import RunAgen
