Comparison

Frameworks build the agent. Everstack runs it.

LangGraph, CrewAI, Mastra, Flue, and the OpenAI Agents SDK define agent logic. Everstack supplies the self-hosted gateway, isolated execution, memory, telemetry, evaluations, and deployment layer around that logic.

Bring your framework

Everstack is framework-agnostic. Point any of these at the gateway and run them on infrastructure you own.

LangGraphLangGraph
CrewAICrewAI
MastraMastra
FlueFlue
OpenAI Agents SDKOpenAI Agents SDK
Vercel AI SDKVercel AI SDK

your framework → runs on Everstack → gateway · sandboxes · memory · observability · evals · deploy

Framework vs platform

What an agent framework gives you, versus what Everstack runs underneath.

CapabilityAgent frameworksEverstack
Authoring: what frameworks are built for
Agent loop, tools, multi-agent
Subagents / delegation
MCP tool integrationMost
Infrastructure: yours to build, or Everstack's
Model gateway: routing, fallback, cache, spend
Sandboxed code executionSome
Durable execution / resumeSome
Persistent memory storeVaries
Self-hosted runtime + deploymentYou operate
Language-agnostic surfacePer-SDK
Operations: running it in production
Built-in observability & tracesOften paired SaaS
EvaluationsAdd-on
Human-in-the-loop approvalDIY
Multi-tenant controls

Framework capabilities vary; values reflect the category as of June 8, 2026. Several frameworks pair with a separate SaaS for observability or evals.

Frequently asked questions

Does Everstack replace my agent framework?

No, and it doesn't try to. Frameworks like LangGraph, CrewAI, Mastra, and Flue are how you express agent logic in code. Everstack is the production layer beneath them: gateway, sandboxes, memory, observability, evals, and deployment. Keep your framework; run it on Everstack.

How do I run my framework on Everstack?

Point the framework's model calls at the Everstack gateway and route tool/code execution to Everstack sandboxes. You get routing, fallback, caching, traces, evals, and approval gates without rewriting your agent.

Frameworks already have some of this, right?

Some do, in pieces: LangGraph has persistence, the OpenAI Agents SDK has tracing, Flue has sandboxes and durable execution. The gap is the platform layer as one self-hosted backend, a multi-provider gateway, built-in evals and approvals, and multi-tenant controls, rather than assembling each piece yourself.

Which framework should I use with Everstack?

Whichever fits your team. Everstack is framework-agnostic by design, so the decision of how you author agents stays yours; Everstack just makes the result production-grade and self-hosted.

Open-source AI infrastructure

Ship the AI stack
you can actually operate.

Start with one model call. Add agents, sandboxes, evaluations, memory, and traces without replacing the foundation underneath them.

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