Head to head
LangGraph vs Mastra
Both are open-source agent frameworks with a real TypeScript story on one side and a real Python story on the other. Mastra is TypeScript-native from day one with batteries-included agents, workflows, and memory; LangGraph is a Python-first graph runtime that also ships a JavaScript port. The decision is which language your team is already standardized on, not which framework is more capable.
On this page
LangGraph and Mastra are both open-source frameworks for building AI agents, and they sit at the same addressable intersection: a team that wants to write its own agent code rather than rent a hosted agent platform. What separates them is the stack they were built for and the shape they expect you to write.
LangGraph is a Python-first graph runtime. An agent is a cyclical graph of nodes and edges, with conditional branches and loops, and state checkpointed after every node transition under a thread_id. That makes it strong where a production agent has to survive a process restart, replay from any earlier checkpoint, or pause mid-run for human review. The same engine runs underneath LangChain's own quick-start `create_agent` harness, and production deploys sit on LangSmith, which adds tracing, evaluation, deployment, an LLM Gateway, and a no-code builder called Fleet. Pricing is $0/seat/month on Developer (5,000 traces), $39/seat/month on Plus (10,000 traces plus one free Serverless Small deployment), and custom on Enterprise, with usage-based LCU ($1.50 each) and LSU ($1.00 each) metering on top. Independent reviewers cite a steep learning curve, and the docs are split across the LangGraph, LangChain and LangSmith sites. A JavaScript port exists, but the canonical design and the production case studies (Klarna, LinkedIn, Uber and Elastic on the vendor's trusted-by strip) are Python.
Mastra is TypeScript-native. It was founded in 2024 by Sam Bhagwat, co-founder of Gatsby, raised a $22M Series A led by Spark Capital on April 9, 2026 ($35M total raised), and is Apache 2.0-licensed at the core. Where LangGraph asks you to compose a graph by hand, Mastra ships agents, durable typed workflows with retries and branching, observational and semantic memory, evals, metrics, traces and a server layer as one package. A model router abstracts OpenAI, Anthropic, Gemini and 180 other providers (6,772 models) behind one interface, with automatic fallback across providers. Built-in deployers target Vercel, Netlify and Cloudflare out of the box, and a separate Mastra Cloud platform adds a hosted Studio, observability and deployment. Self-hosted Apache 2.0 is free; Mastra Cloud Starter is free with 100K observability events and 24 CPU hours included; Teams is $250/month with 1M events, 250 CPU hours, SSO and SOC 2 docs; Enterprise and Enterprise Self-Hosted are custom. There is no Python variant at all, the Enterprise RBAC, SSO and IAM controls are gated behind a source-available Enterprise license rather than the Apache 2.0 core, and the ecosystem is younger: Mastra's 27.4K GitHub stars against LangChain's 142K+ reflect a multi-year gap.
The decision is rarely about raw capability. It is about which language your team is already standardized on. A Python shop building a long-running, stateful production agent with checkpointed replay and human review leans LangGraph, accepts the learning curve, and gets the LangSmith production layer with it. A TypeScript shop (Next.js, Node, serverless on Vercel or Cloudflare) leans Mastra, gets batteries-included without a separate Python service, and ships a working agent in a single framework. There is no third option: LangGraph's own not-for calls out "building a lightweight TypeScript app on serverless infrastructure where a framework like Mastra fits the deploy target better", and Mastra's own not-for calls out "Python-first teams and anyone needing a mature, multi-year-proven ecosystem".
How LangGraph and Mastra compare
| Feature | LangGraphVisit LangGraph ↗ | MastraVisit Mastra ↗ |
|---|---|---|
| Description | Open-source orchestration framework and runtime for stateful, long-running LLM agents, from LangChain. | Open-source TypeScript framework for building AI agents, with a hosted platform for running and observing them. |
| Pricing | free, then $39/month | free, then $250/month |
| Pricing model | freemium | freemium |
| Model / LLM | OpenAI, Anthropic, Google, AWS Bedrock, Groq, Ollama and more | Model-agnostic (180 providers, 6,772 models) |
| Bring your own model | Yes | - |
| Interface | Library | Library |
| Deployment | Both | Both |
| Debugs and fixes | Partly (LangSmith Engine add-on) | - |
| Done-for-you service | No | Partly (Mastra Concierge / Enterprise Support add-on) |
| Agent permissions | Partly | Yes |
| In your pipeline | Yes | Partly |
| Seat model | Yes | No |
| Admin controls | Partly (Enterprise plan and up) | Partly (Mastra Enterprise Edition plan and up) |
| Single sign-on | Partly (Enterprise plan and up) | Partly (Teams plan and up) |
| Data residency | Partly (Plus plan and up) | Partly (Enterprise (self-hosted) plan and up) |
| Getting out | Partly (Enterprise plan and up) | Partly |
| Certifications | Yes | Partly (Teams plan and up) |
| Limitations |
|
|
Who each one is for
LangGraph
Engineering teams building production agents who need cyclical graphs, durable state and replayable runs
From Free
Mastra
Full-stack JavaScript and TypeScript teams, especially those already building in Next.js or Node, who want agents, durable workflows and memory unified in one framework without adopting a Python-first stack.
From Free
Verdict: LangGraph or Mastra?
Choose LangGraph if your team is standardized on Python, you are building a long-running production agent that has to survive restarts and replay from prior checkpoints, and you want the LangSmith deployment and tracing layer behind it. Choose Mastra if you are a full-stack TypeScript or JavaScript team shipping on Next.js, Node or serverless, and you want agents, durable workflows, memory and observability unified in one framework without a separate Python service.
The digest
New agents and articles, by email, at most once a week.
Frequently asked questions
- Is LangGraph the same as LangChain?
- No. LangGraph is a separate open-source, MIT-licensed library, but it is built and maintained by LangChain Inc. and is the runtime underneath LangChain's higher-level `create_agent` harness. LangSmith is the production platform that sits next to both for tracing, evaluation, deployment, an LLM Gateway and a no-code builder called Fleet.
- Can Mastra replace LangGraph in a Python project?
- No. Mastra is TypeScript-only, with no Python variant at all. A Python team that wants this kind of unified agent framework surface has to pick LangGraph or another framework that ships both languages. LangChain itself, LlamaIndex or the OpenAI Agents SDK all ship a Python variant alongside their JavaScript bindings.
- Which framework has lower total cost for a small team?
- Self-hosted Mastra is free on Apache 2.0; self-hosted LangGraph is free on MIT. Once you add production: LangGraph Plus is $39/seat/month with usage-based LCU ($1.50 each) and LSU ($1.00 each) metering on top; Mastra Cloud Starter is free up to 100K observability events and 24 CPU hours, with Teams at $250/month. A small TypeScript team usually spends less on Mastra Cloud than a small Python team spends on LangGraph Plus once trace and deployment metering starts.
- Does Mastra run on Vercel or Cloudflare Workers?
- Yes. Mastra ships built-in deployers for Vercel, Netlify and Cloudflare, and integrates directly into an existing Next.js app. LangGraph's managed LangSmith deployment is not designed for those serverless targets, which is one of the reasons LangGraph itself lists Mastra as the right fit in its not-for.
- Which has the larger ecosystem today?
- LangGraph, by a wide margin: it ships on top of LangChain's mature 142K+ GitHub-star ecosystem and a multi-year track record of named production users (Klarna, LinkedIn, Uber and Elastic on the vendor's trusted-by strip). Mastra is younger (founded 2024) with 27.4K GitHub stars and a shorter production reference list (Salesforce, Replit, Sanity, SoftBank, MongoDB, Brex and Factorial), but it has commercial backing from a $22M Series A led by Spark Capital.
Related comparisons and alternatives
Still deciding? Get a quote from LangGraph or Mastra
Choose a provider and tell them what you need.
The digestFree
Which agents actually ship.
New agents and articles, by email, at most once a week.
One-click unsubscribe
At a glance
Both are open-source agent frameworks with a real TypeScript story on one side and a real Python story on the other. Mastra is TypeScript-native from day one with batteries-included agents, workflows, and memory; LangGraph is a Python-first graph runtime that also ships a JavaScript port. The decision is which language your team is already standardized on, not which framework is more capable.