LangChain
Open-source Python/JS framework for composing LLMs, tools, and memory into applications and agents.
Last verified:
LangChain is a free, MIT-licensed open-source framework for building LLM-powered applications, chaining together models, vector stores, tools, and third-party integrations. It is maintained by LangChain Inc., the San Francisco company that also builds LangGraph (agent orchestration) and LangSmith (the paid observability/deployment platform). LangChain Inc. was founded in early 2023 by Harrison Chase and Ankush Gola, and raised a $125M Series B in October 2025 at a $1.25B valuation.
Pricing
| Tier | Price | Key features |
|---|---|---|
| Open Source (LangChain Framework) | $0 | Free Python and JS/TS libraries, Model, vector store, and tool integrations, No usage caps or seat limits, No account required to use the library |
Source: https://www.langchain.com/pricing
Agent-readiness
- Discoverability
- 68/100
- Machine-readable content
- 88/100
- Programmatic access
- 92/100
- MCP / agent support
- 25/100
- Self-serve transactability
- 95/100
- Transparency
- 60/100
Security & compliance
- SSO / SAML
- Not publicly documented
- Encryption at rest
- Not publicly documented
- Encryption in transit
- Yes
- Audit log
- Not publicly documented
- Pentest report
- Not publicly documented
"Not publicly documented" means Crail found no public evidence either way — not a confirmed absence. See our methodology. Trust center: https://trust.langchain.com.
FAQ
Does LangChain have a free tier?
Yes, LangChain offers a free tier or free trial.
Can you buy LangChain without talking to sales?
Yes, LangChain can be purchased self-serve without a sales call.
Does LangChain have an official MCP (Model Context Protocol) server?
Not as of 2026-07-27 — no official MCP server was found.
Reviews
No reviews yet for LangChain. Be the first to submit a verified review.
Methodology & disclosure
Data verified via agent crawled, last checked 2026-07-27. Agent-readiness methodology version crail-ar-v0.1. No vendor payment influences these scores — see our methodology page.