DeepYard

LangChain vs Mastra

Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.

Direct Answer

LangChain suits teams needing open-source access, python focus, and 144,745 GitHub stars in current listing data. Mastra suits teams needing open-source access, multi agent focus, and 27,357 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.

What this comparison weighs

  • Pricing and free-tier availability
  • License model and deployment fit
  • GitHub adoption and contributor depth
  • Catalog tags, integrations, and supported workflows
L

LangChain

Build context-aware reasoning applications with LLMs

OSSFree
144.7K850.0K/wtoday467
Visit GitHub
M

Mastra

TypeScript framework for building AI agents and workflows

OSSFree
27.4K12.0K/wtoday465
Visit GitHub
MetricLangChainMastra
GitHub Stars144.7K27.4K
Contributors467465
Last CommitAug 22, 2026Aug 22, 2026
Open Issues416523
Licenseopen-sourceopen-source
Pricingopen-sourceopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Choose LangChain if you need

  • • LangChain stands out for Python workflows that are not listed for Mastra.
  • • LangChain is the stronger pick when Chain matters because that capability is listed only on its profile.
  • • LangChain shows broader GitHub adoption with 144,745 stars versus 27,357 for Mastra.

Choose Mastra if you need

  • • Mastra is the stronger pick when Multi Agent matters because that capability is listed only on its profile.
  • • Mastra is the cleaner fit if you specifically need Workflows workflows from the catalog tags.

Meaningful differences

  • • Workflow emphasis: LangChain highlights Python, while Mastra highlights Typescript.
  • • GitHub adoption: LangChain shows 144,745 stars versus 27,357 for Mastra.
  • • Contributor count: LangChain lists 467 contributors and Mastra lists 465.

Shared capabilities

  • • Agents
  • • Rag
  • • Typescript

Shared Tags

agentsragtypescript

Only in LangChain

llmchainspythonorchestration

Only in Mastra

workflowsmulti-agentopen-source

Limitations and evidence

  • • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
  • • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
  • • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.

Source links

Manifest content date: 2026-08-21

About LangChain

LangChain is the most widely adopted framework for building LLM-powered applications. It provides modular abstractions for chains, agents, memory, retrievers, and tools, enabling developers to compose complex pipelines from reusable components. Available in both Python and JavaScript/TypeScript, LangChain integrates with every major LLM provider, vector store, and data source. Its ecosystem includes LangSmith for observability and LangGraph for stateful, graph-based agent workflows.

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About Mastra

Mastra is a TypeScript-first framework for building AI agents, workflows, and RAG pipelines. It provides a unified interface for connecting to LLMs, managing tools, and orchestrating multi-step agent workflows with built-in observability. Mastra emphasizes developer experience with type-safe APIs, local development tools, and seamless deployment to serverless environments.

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