DeepYard

Agno vs LangChain

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

Direct Answer

Agno suits teams needing open-source access, agents focus, and 41,830 GitHub stars in current listing data. LangChain suits teams needing open-source access, typescript focus, and 144,745 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
A

Agno

Build, run, and manage agentic software at scale with 38K+ stars

OSSFree
41.8Ktoday444
L

LangChain

Build context-aware reasoning applications with LLMs

OSSFree
144.7K850.0K/wtoday467
MetricAgnoLangChain
GitHub Stars41.8K144.7K
Contributors444467
Last CommitAug 22, 2026Aug 22, 2026
Open Issues1276416
Licenseopen-sourceopen-source
Pricingopen-sourceopen-source
Free TierYesYes
Categoryframeworksframeworks
TrendingNoNo

Choose Agno if you need

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

Choose LangChain if you need

  • LangChain stands out for Typescript workflows that are not listed for Agno.
  • 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 41,830 for Agno.

Meaningful differences

  • Workflow emphasis: Agno highlights Python, while LangChain highlights Typescript.
  • GitHub adoption: Agno shows 41,830 stars versus 144,745 for LangChain.
  • Contributor count: Agno lists 444 contributors and LangChain lists 467.

Shared capabilities

  • Python
  • Orchestration
  • Rag
  • Memory

Shared Tags

pythonorchestrationrag

Only in Agno

agent-frameworkfastapimulti-agenttool-usememoryopen-sourceself-hosted

Only in LangChain

llmagentschainstypescript

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.

About Agno

Agno is a full-stack platform for agentic software comprising three layers: a Python framework for building agents and teams with memory, knowledge, and 100+ tool integrations; a production-ready FastAPI runtime with 50+ APIs, horizontal scaling, native tracing, and human-in-the-loop approval workflows; and AgentOS, a control plane UI for monitoring and managing deployed agents. Supports per-user and per-session isolation, role-based access control, guardrails, evaluations, and immutable audit trails. All data stays in your database — no vendor lock-in.

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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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