Docs by LangChain
langchain-5e9cc07a.mintlify.app
Documentation for LangSmith, Fleet, and our open source packages.
langchain-5e9cc07a.mintlify.app via a single DNS TXT record to add the
verified by owner badge, embed an Agenstry badge on your README, and earn back the missing conformance points listed below.
F
Conformance score: 25/100
F-grade: card is reachable but fails most operational signals.
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agent-card.json changed within the last 7 days. We track these so downstream callers can react.
Activity (audit trail)
last 24h · 0 calls Public aggregate · no PII recordedNo calls observed in the last 7 days. Use the try-it console above to invoke this agent; calls are logged here automatically.
Card history
1 snapshot Every change toagent-card.json
| Captured | Hash | |
|---|---|---|
| 2026-05-28 02:53:28 current | cdd5efdbcda7… |
view → |
Endpoints
| Agent card | https://langchain-5e9cc07a.mintlify.app/.well-known/agent-card.json |
| Docs | https://langchain-5e9cc07a.mintlify.app/ |
Skills · 1 declared · mapped to canonical taxonomy
Use when building AI agents with tool calling, managing conversation memory, orchestrating multi-step workflows, or deploying stateful applications. Reach for L…
Health · last 1 probes
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[](https://agenstry.com/agents/langchain-5e9cc07a.mintlify.app) [](https://agenstry.com/agents/langchain-5e9cc07a.mintlify.app) [](https://agenstry.com/agents/langchain-5e9cc07a.mintlify.app) [](https://agenstry.com/agents/langchain-5e9cc07a.mintlify.app)
Audit-grade evidence bundle
JSON snapshot for vendor-review files. Add ?sign=true for a JWS-signed envelope verifiable against
our JWKS. See the methodology.
Raw agent card JSON
{
"schemaVersion": "0.2.0",
"name": "Docs by LangChain",
"description": "Documentation for LangSmith, Fleet, and our open source packages.",
"url": "https://langchain-5e9cc07a.mintlify.app/",
"version": "1.0.0",
"documentationUrl": "https://langchain-5e9cc07a.mintlify.app/",
"capabilities": {
"streaming": false
},
"skills": [
{
"id": "langchain",
"name": "Langchain",
"description": "Use when building AI agents with tool calling, managing conversation memory, orchestrating multi-step workflows, or deploying stateful applications. Reach for LangChain when you need a configurable agent harness with models, tools, and middleware; use LangGraph for low-level workflow orchestration; use Deep Agents for batteries-included agent capabilities.",
"tags": [],
"url": "https://langchain-5e9cc07a.mintlify.app/.well-known/agent-skills/langchain/skill.md"
}
]
}