Comparison

Everstack vs Mastra

Mastra is the best-adopted TypeScript agent framework and a well-funded one. The comparison that matters is not feature by feature, it is shape: Mastra is the code you write an agent in, and Everstack is the platform that sits in front of agents written in anything. For a Mastra team the honest answer is often both.

EverstackEverstack
vs
MastraMastra
View pricingRead documentation

What is Mastra?

Mastra is a TypeScript framework for building AI agents, with agents, workflows, memory, RAG, scorers and a visual Studio, built on the Vercel AI SDK by the team behind Gatsby. It has 28,187 GitHub stars and 1.19M weekly npm downloads as of 19 September 2026, and $35M in funding. The core is Apache-2.0; code under ee/ directories is under a separate Enterprise Edition licence.

Why teams choose Everstack

  • Works with agents written in any language or framework: traffic goes through an OpenAI-compatible gateway and traces arrive over OpenTelemetry
  • Apache-2.0 across the repository, with no enterprise directory under a separate licence
  • Runs isolated sandboxes itself on Docker, Firecracker or Kubernetes rather than through a third-party sandbox vendor

Mastra: Strengths & Limitations

Strengths

  • The strongest TypeScript agent framework by adoption: 28,187 GitHub stars and 1,187,203 weekly downloads of @mastra/core in the week to 18 September 2026.
  • Batteries included for building an agent from scratch: agents, workflows with branching and human approval, memory, RAG, scorers, datasets and a visual Studio, in one package.
  • Built on the Vercel AI SDK, so it reaches 40+ providers and integrates naturally with Next.js, SvelteKit, Astro, Express and Hono applications.
  • First-class MCP client and server support, and Agent2Agent protocol support in both directions.
  • Well funded and well referenced: $35M raised, with Brex, Indeed, Marsh McLennan, MongoDB, Workday and Salesforce named as customers in the Series A announcement.

Limitations

  • TypeScript only. There is no Python SDK, and an agent built in LangGraph, the Google ADK, the Claude Agent SDK or plain Python is outside its model.
  • The licence is split. Code under any ee/ directory is governed by the Mastra Enterprise Edition licence, effective 24 August 2026, which permits development and testing but requires a paid agreement for production use.
  • Observability is documented for Mastra's own agents, workflows, tools and model calls. We could not find documentation for ingesting traces from applications that are not built on Mastra.
  • Sandboxes are provided through Daytona, E2B and Blaxel rather than run by Mastra, so isolated execution is a second vendor relationship.

Everstack advantage

Any framework, any language, one traceOne Apache-2.0 licence, no ee/ directorySandboxes run by the platform itselfA Mastra agent can route through Everstack today

The facts, side by side

Licence, deployment model and list price, taken from each vendor's own documentation. Every source is linked at the bottom of this page.

FactEverstackMastra
What it isA self-hosted platform: an OpenAI-compatible gateway, an agent runtime, isolated sandboxes, evaluations and OpenTelemetry observability, in front of agents written in anything.A TypeScript framework for writing agents, with a hosted platform (Studio, Server, observability) built around agents written in it.
LicenceApache-2.0 across the repository.Apache-2.0 for the core since July 2025, previously Elastic License 2.0. Code under ee/ directories is under the Mastra Enterprise Edition licence v1.0, effective 24 August 2026. GitHub reports the repository licence as NOASSERTION for this reason.
LanguagesAny. Applications call an OpenAI-compatible endpoint and emit OpenTelemetry; SDKs exist for Node and Python.TypeScript only.
Observability for agents not built on itYes. Traces arrive over OTLP from any instrumented application, and gateway traffic is traced without instrumentation.Documented for Mastra agents, workflows, tools and model calls, with pluggable storage (ClickHouse, PostgreSQL, MongoDB and others). Ingestion from non-Mastra applications is not documented.
Isolated code executionDocker, Firecracker and Kubernetes sandboxes run by the platform.Remote Sandboxes through Daytona, E2B or Blaxel, each with its own filesystem, network and process space.
Published pricingPublished on the pricing page; self-hosting is free under Apache-2.0.Starter free with 100K observability events a month, Teams $250 a month with 1M events, Enterprise custom. Self-hosted open source free; self-hosted Enterprise a custom flat annual fee (19 September 2026).
ProtocolsMCP server endpoint on the gateway. No A2A today.MCP client and server, and Agent2Agent v0.3 and v1.0 with agent-card discovery.
Community sizeSmall. Mastra wins this by a wide margin.28,187 GitHub stars and 1,187,203 weekly npm downloads of @mastra/core (19 September 2026).

Licence read from the root LICENSE and ee/LICENSE files in mastra-ai/mastra and mastra.ai/docs/community/licensing; pricing from mastra.ai/pricing; stars from the GitHub API and downloads from the npm API, all on 19 September 2026. Where Mastra's documentation does not describe a capability we say so rather than assume it is absent.

Feature comparison

Direct capability comparison across key dimensions

FeatureEverstackMastra
Building agents
Agent definition SDKAgents as code, plus any external frameworkTypeScript SDK
Workflows with branching and approvals
Memory and RAG
Python or Go agents
Gateway
OpenAI-compatible endpoint any app can callMastra Gateway, priced at market rate plus 5.5%
Multi-provider routingThrough the Vercel AI SDK, 40+ providers
Virtual keys, budgets and per-tenant limits
Observability
Traces, metrics and logs for its own agents
OTLP ingestion from agents built elsewhereNot documented
Datasets, scorers and evaluations
Execution
Isolated sandboxesDocker, Firecracker, Kubernetes, run by the platformDaytona, E2B or Blaxel
Protocols
MCPServer endpointClient and server
Agent2Agent
Deployment
Self-hosted single binaryNode.js server built with mastra build; Studio self-hostable
Managed cloud
Licence
One licence across the repository
Ecosystem
Community size and worked examples

The same job, in both products

Working code rather than adjectives. Each snippet follows the quickstart published by the product it belongs to.

Define an agent and call a model

Mastra is the code you write the agent in. Everstack is the endpoint the agent's model calls go through, whatever the agent is written in. The two are different layers, which is why they compose.

Everstack

agent.ts
import OpenAI from "openai";// Any framework, any language: point the model call at Everstack.const client = new OpenAI({  baseURL: "https://{instance}.{region}.everstack.ai/openai/v1",  apiKey: process.env.EVERSTACK_API_KEY,});const response = await client.chat.completions.create({  model: "gpt-4o-mini",  messages: [{ role: "user", content: "Summarise this report" }],});

Mastra

agent.ts
import { Agent } from "@mastra/core/agent";// The agent is a Mastra object; the model is resolved through the AI SDK.export const summariser = new Agent({  name: "summariser",  instructions: "Summarise reports concisely.",  model: "openai/gpt-4o-mini",});const result = await summariser.generate("Summarise this report");

Key evaluation questions

What to ask when comparing Mastra to Everstack

QuestionEverstackMastra
Can it observe an agent written in Python?Yes, over OTLP or by routing its model calls through the gateway.Not that the documentation describes. Observability is for Mastra agents.
Is production use of every feature covered by the open source licence?Yes. Apache-2.0 across the repository.Not for code under ee/ directories, which needs a paid agreement in production.
Who runs the sandbox?The platform, on Docker, Firecracker or Kubernetes.Daytona, E2B or Blaxel, through Mastra's sandbox interface.
Which has the bigger community?Not this one.Mastra, by a wide margin.

Feature-by-feature analysis

Where each product is genuinely stronger, row by row

Framework or platform

Close call
Everstack

A platform in front of agents: gateway, runtime, sandboxes, evaluations and traces, with the agent written in whatever the team already uses.

Mastra

A framework the agent is written in, with a platform built around agents written that way.

How to choose

This is the whole comparison. If every agent you will ever run is TypeScript, Mastra's shape is simpler. If some are Python, Go, or built on another framework, a platform that sits in front of all of them is the only one that gives you one trace.

Where the licence line falls

Everstack wins
Everstack

Apache-2.0 across the repository, including enterprise features.

Mastra

Apache-2.0 core with ee/ directories under a separate Enterprise Edition licence that permits development and testing but not production use without a paid agreement.

Why Everstack

Both are honest and both are open source at the core. The question is whether the feature you need is under ee/, and that list is Mastra's to change.

Observability for what you already run

Close call
Everstack

OTLP ingestion from any instrumented application, and gateway traffic traced without instrumentation.

Mastra

Deep traces for Mastra agents, workflows and tools, with pluggable storage and export to OpenTelemetry destinations.

How to choose

Mastra's view of a Mastra agent is richer than a gateway can be. Everstack's view covers agents Mastra never sees. Which matters depends on how many of your agents are Mastra agents.

Isolated execution

Everstack wins
Everstack

Docker, Firecracker and Kubernetes sandboxes run by the platform, billed by the platform.

Mastra

Remote Sandboxes through Daytona, E2B or Blaxel.

Why Everstack

Both give agents an isolated filesystem, network and process space. With Mastra it is a second vendor with its own pricing and data path; with Everstack it is the same control plane.

Ecosystem and mindshare

Mastra wins
Everstack

Young, small community, fewer worked examples.

Mastra

28,187 stars, 1.19M weekly downloads, $35M raised, and enterprise references. When a TypeScript team asks which agent framework to use, this is the answer they get.

Why Mastra

Ecosystem gravity compounds, and Mastra has a lot of it. It is the most durable advantage in this comparison and it is not Everstack's.

Moving from Mastra to Everstack

This is not usually a migration. Mastra is the framework an agent is written in; Everstack is the gateway and observability in front of it. Mastra resolves models through the Vercel AI SDK, and the AI SDK's OpenAI provider accepts a custom base URL, so a Mastra agent can send its model traffic through Everstack and appear in Everstack traces without leaving Mastra. Moving an agent off Mastra entirely means rewriting it, in either direction.

  1. 1

    Route the model calls

    Construct the AI SDK OpenAI provider with Everstack's OpenAI-compatible base URL and an Everstack API key, and give that provider's model to the Mastra agent.

  2. 2

    Send the traces

    Mastra's observability is built on OpenTelemetry and can export to OpenTelemetry-compatible destinations. Point that export at Everstack's OTLP endpoint to see the agent's spans next to its gateway traffic.

  3. 3

    Decide what runs where

    Keep memory, workflows and Studio in Mastra if the team is happy there. Use Everstack for the parts Mastra hands to someone else: sandboxes it runs itself, per-tenant keys and budgets, and agents written in other languages.

  4. 4

    Only then consider replacing the framework

    If the goal is one runtime for agents in several languages, port the agent definitions to Everstack's agent runtime. Budget it as a rewrite, because it is one.

What breaks

  • Mastra workflows, memory and Studio have no drop-in Everstack equivalent; an agent that depends on them stays in Mastra or is rewritten.
  • Anything under a Mastra ee/ directory used in production needs a paid Mastra agreement, whichever gateway sits in front of it.
  • Mastra's A2A support has no Everstack counterpart today.

What does not carry over

  • Mastra Cloud observability history and datasets.
  • Mastra Memory Gateway state and observational memory.
  • Studio configuration and deployments.

Read this part first

When to choose Mastra instead

Mastra is the best-adopted TypeScript agent framework and for a lot of teams it is the right starting point. Pick Mastra over Everstack when any of these is true.

  • You are a TypeScript team building new agents and want a framework with agents, workflows, memory, RAG and evals in one package. Everstack is not a framework and does not want to be one.
  • You live in the Vercel ecosystem. Mastra is built on the AI SDK and deploys to Vercel, Netlify and Cloudflare with adapters.
  • You want the largest community. 28,187 stars and over a million weekly downloads mean more examples, integrations and answered questions than any younger project has.
  • You need Agent2Agent today. Mastra supports it in both directions; Everstack does not.
  • You want a managed platform priced per observability event with a free starter tier and unlimited users. That is Mastra Cloud's model.
  • You have no agents outside TypeScript and no requirement to run sandboxes yourself. Then the things Everstack adds are things you do not need.

Frequently asked questions

Common questions about choosing between Everstack and Mastra

Ready to get started?

See how Everstack compares to Mastra for your specific use case.

View pricingRead docs

Sources & References

Mastra licensingMastra Enterprise Edition licenceMastra pricingMastra observabilityMastra Remote SandboxesMastra Series Amastra-ai/mastra repositoryEverstack licence (Apache-2.0)

Last reviewed: September 19, 2026. This comparison is for informational purposes and reflects our understanding of competitor capabilities based on publicly available documentation.

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