Product

LangChain

by LangChain

Product website
https://www.langchain.com
Documentation
https://docs.langchain.com
Categories
AI Developer Tooling

Description

Framework for building agents and LLM applications with interoperable components and provider integrations.

AI-native score

How ready this product is for agents to use, on a 0–100 scale across four weighted dimensions. Security is one of them, so a high score is not a substitute for your own security or vendor-risk review. How is this scored?

Unrated. Only 19% of the scored decision fields are researched, so the grade is held until more are confirmed. The breakdown below shows what's been scored.

Integration3/10Trust0/6Portability3/4Security0/4Tier D26/100
Component Raw Weight Contribution
Integration 3/10 35% 10.5
Trust 0/6 30% 0.0
Portability 3/4 20% 15.0
Security 0/4 15% 0.0
Signals that fired
  • Integration: MCP server (+2) ; SDK / developer kit (+1)
  • Portability: Open standards (+1) ; Self-hostable (+1) ; Open source (+1)
Signals not researched

These gaps cover the fields used in the AI-native score.

  • Integration surfaces: llms.txt, WebMCP, Headless signup, Agent2Agent (A2A) servers, Native connectors, API specs, Command-line interfaces, Agent skills
  • Trust & data policy: Trust center, Multi-factor authentication, Zero data retention, No generative AI training, Hard budget caps, Sandbox environment, Data export, Data import, Standard protocol access, No proprietary-SDK lock-in, Documented provider swap
  • Security & compliance: Compliance certifications, Access controls

Trust & data policy

Open standards
Yes
Self-hostable
Yes
Open source
Yes
Source code
https://github.com/langchain-ai/langchain

Not yet researched Trust center, Multi-factor authentication, Zero data retention, No generative AI training, Hard budget caps, Sandbox environment, Data export, Data import, Standard protocol access, No proprietary-SDK lock-in, Documented provider swap

What it does

Jobs to be done

  • Build AI agents

    Develop applications in which language models use tools and context to carry out tasks.

    View 6 products

Integration surfaces

How an agent connects to this product and finds its documentation. The largest dimension of the AI-native score (35%).

MCP servers

Model Context Protocol endpoints an AI agent can connect to for this product's tools and data.

Developer kits

Not yet researched llms.txt, WebMCP, Headless signup, Agent2Agent (A2A) servers, Native connectors, API specs, Command-line interfaces, Agent skills

Offers

No offers recorded.

Reviews

No approved reviews yet.

RSS: approved reviews

Catalog activity

Track how this entry changes as proposals are opened and merged.

RSS: merged changes · RSS: open proposals

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Ready to decide?

Unrated · 19% researched. Grade withheld until more fields are verified.

Visit LangChain