Backend for AI Agents

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xpander.ai is Backend-as-a-Service for autonomous agents. It abstracts the ops layer so AI engineers focus on behavior and outcomes. You get managed agent hosting with version control and CI/CD, a fully managed PostgreSQL memory layer, and a curated library of 2,000+ functions, including MCP Tools and the MCP Generator.

Our AI native triggering system post-processes inputs from MCP, agent-to-agent, API, and web, then delivers a single unified message to your agent so you never deal with wiring or formats. xpander works with any agent framework or SDK, with native support for Agno and OpenAI.

Feature	Description
🛠️ Framework Flexibility	Choose from popular frameworks like OpenAI ADK, Agno, CrewAI, LangChain, or work directly with native LLM APIs
🧰 Tool Integration	Access our comprehensive MCP-compatible tools library and pre-built integrations
🚀 Scalable Hosting	Deploy and scale your agents effortlessly on our managed infrastructure
💾 State Management	Opt for framework-specific local state or leverage our distributed state management system
⚡ Real-time Events	Harness our event streaming capabilities for Slackbots, ChatUIs, Agent2Agent communication, and Webhook integrations
🛡️ API Guardrails	Implement robust guardrails using our Agent-Graph-System to define and manage dependencies between API actions of tool-use

By abstracting away infrastructure complexity, xpander.ai empowers you to focus on what matters most: building intelligent, effective, production-ready AI agents.

⭐ Featured template - fully-featured cloud-based SWE agent with Claude Code

1. Template url
2. Send tasks to the agent.
   Examples:

   Clone the <my-repo-name> repo and add the following feature to the codebase ..., then create a PR with the new code.
   

   Find all open PRs that have been waiting on review for more than 3 days.
   

3. Continue customizing, adding tools, configure triggering (MCP, A2A, Webhooks), multi-agent collaboration, and more.

Adding a backend to your agents in less than 5 minutes

📦 Installation

# Python
pip install xpander-sdk

# Node.js
npm install @xpander-ai/sdk

# CLI (for agent creation)
npm install -g xpander-cli

Use xpander-cli to scaffold a new agent template

xpander login
xpander agent new

Prepare virtual env

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Develop the agent and run it

xpander dev

Bring your AI agent code and stream events to your agent

Add one line of code to xpander_handler.py and your agent will be accessible via Agent2Agent, Slackbots, MCP servers, or WebUI.

from xpander_sdk import Task, Backend, on_task
from agno.agent import Agent

# Stateful agent, zero infrastructure overhead
@on_task
async def handle_task(task: Task):
  backend = Backend() # DB, MCP tools, system prompt
  agent = Agent(**await backend.aget_args())

  # Task includes user data + events from Slack, webhooks, agents
  result = await agent.arun(message=task.to_message())
  task.result = result.content
  return task

Deploy agent to the cloud

xpander deploy  # Will deploy the Docker container to the cloud and run it via the xpander_handler.py file
xpander logs    # Will stream logs locally from the agent configured locally

🧩 Getting Started Examples

simple-hello-world

📚 Documentation & Resources

• Documentation
• API Reference
• Discord Community

⚖️ License

• Open-source runtime: Apache License 2.0
• Hosted platform: Commercial (free tier available)

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