head to head · open source
langchain vs agents-best-practices
langchain has 148,892 GitHub stars, 25,031 forks, 492 open issues and last shipped yesterday. agents-best-practices has 2,411 stars, 217 forks, 6 open issues and last shipped 15 days ago. langchain leads on adoption by 6,076% (148,892 vs 2,411 stars). langchain is written in Python under MIT; agents-best-practices is written in various languages under MIT. langchain has attracted 17% as many forks as stars, agents-best-practices 9%. langchain was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (agents, ai-agents, anthropic), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| langchain | agents-best-practices | |
|---|---|---|
| GitHub stars | ★ 149K | ★ 2.4K |
| License | MIT | MIT |
| Written in | Python | — |
| Last push | 2026-11-02 | 2026-10-19 |
| Forks | ⑂ 25K | ⑂ 217 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick langchain if
- You weight community size — 149K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick agents-best-practices if
- You want the agents-best-practices feature set and don't need the biggest community
- You prefer the MIT license terms
- You evaluated both and agents-best-practices fits your workflow better
About langchain
The agent engineering platform. LangChain is a framework for building agents and LLM powered applications. It helps you chain together interoperable components and third party integrations to simplify AI application development — all while future proofing decisions as the underlying technology evolves. [!TIP] Just getting started? Check out Deep Agents — a higher level package built on LangChain for agents that have built in capabilities for common usage patterns such as planning, subagents, file system usage, and more. Quickstart If you're looking for more advanced customization or agent orchestration, check…
read the full langchain overview →
About agents-best-practices
agents best practices "The model proposes actions; the harness validates, authorizes, executes, records, and returns observations." A provider neutral Agent Skill for designing, generating MVP blueprints for, auditing, refactoring, and explaining agentic harnesses. It applies beyond coding agents: research, support, operations, sales, finance, data analysis, procurement, legal workflows, healthcare workflows, education, and workflow automation agents all need the same core runtime discipline. Install pick one: A. With skills (any compatible agent): The g flag installs globally at user level so every project can…
read the full agents-best-practices overview →
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Frequently asked questions
Is langchain or agents-best-practices more popular?
langchain has 148,892 GitHub stars and agents-best-practices has 2,411. langchain has the larger community by that measure.
Are langchain and agents-best-practices free?
Both are open source. langchain is licensed under MIT and agents-best-practices under MIT. Neither carries a licence fee.
What is the difference between langchain and agents-best-practices?
langchain is written in Python and agents-best-practices in various languages. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, langchain or agents-best-practices?
Choose langchain if you want the larger community (148,892 stars) or its MIT licence terms. Choose agents-best-practices if its feature set, stack or MIT licence fits better. Both are self-hostable.