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Basic Information

xpander.ai is a framework-agnostic Backend-as-a-Service designed to provide infrastructure for autonomous AI agents. It supplies core backend capabilities such as memory, tool integration, multi-user state, storage, agent-to-agent messaging, and event streaming. The platform supports multiple triggering options including MCP servers, agent-to-agent (A2A) messaging, API endpoints, and web interfaces so agents can be invoked from Slack, webhooks, or chat UIs. It is built to work with popular agent frameworks and SDKs like OpenAI ADK, Agno, CrewAI, LangChain, or directly with native LLM APIs. The repository contains SDKs and CLI tooling for Python and Node, templates for ready-made agents, examples and a minimal code snippet showing how to wire an agent to the backend. The runtime is open-source under Apache 2.0 while the hosted platform is commercial with a free tier.

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Features
The README highlights several concrete features: framework flexibility to integrate with different agent SDKs and LLM APIs, an MCP-compatible tools library and pre-built integrations, managed scalable hosting for running agents, and options for local or distributed state management. Real-time event streaming supports Slackbots, ChatUIs, Agent2Agent communication and webhooks. An Agent-Graph-System provides API guardrails to define and manage dependencies between tool actions. Developer ergonomics include Python and Node package installs, an xpander-cli to scaffold agents and commands such as xpander dev, xpander deploy and xpander logs. The project also ships templates including a featured cloud SWE agent template and examples for getting started.
Use Cases
xpander.ai reduces infrastructure complexity so teams can focus on building and shipping intelligent agents rather than managing backend plumbing. It enables rapid onboarding through SDKs, CLI scaffolding and ready templates so a backend can be added in minutes. The platform centralizes state, tools and messaging, enabling multi-agent collaboration, persistent user state and streamable events from external sources. Guardrails and the Agent-Graph-System help control tool use and API dependencies. Built-in deployment and logging commands simplify running agents in the cloud. The combination of an open-source runtime and a hosted commercial offering provides flexibility for development, testing and production use with a free tier for initial exploration.

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