What Is Agent Stack?
Agent Stack is open infrastructure for deploying AI agents as backend services. It provides a runtime layer for LLM routing, vector storage, authentication, file handling, deployment tooling, and integrations so developers can focus on agent logic instead of plumbing.
It is designed to help teams move from local agent experiments to running services that applications can call reliably.
Key Features of Agent Stack
- Runtime infrastructure for serving AI agents.
- LLM routing, embeddings, vector search, and file services.
- Authentication, secrets management, and deployment tooling.
- MCP integrations and A2A-compatible agent exposure.
- Works with agents built in LangGraph, CrewAI, custom frameworks, and more.
Who Should Use Agent Stack?
Agent Stack is useful for AI engineers, platform teams, and developers who need to deploy agents as real services rather than local scripts.
Agent Stack Pricing
Agent Stack is open infrastructure. Costs depend on hosting, model providers, storage, and deployment choices.