Home / Companies / LangChain / Blog / Post Details
Content Deep Dive

Connections: Managed credentials and per-caller identity for Managed Deep Agents

Blog post from LangChain

Post Details
Company
Date Published
Author
Victor Moreira
Word Count
1,337
Company Posts That Month
6
Language
English
Hacker News Points
-
Post removed?
No
Summary

LangSmith Connections in the Managed Deep Agents prerelease provides named, runtime-resolved credentials that let agents distinguish between permissions and the identity on whose behalf an action is performed, avoiding hard-coded shared API keys and service-account attribution. Connections combine independent ownership and credential-type choices: agent-owned or user-owned credentials can each use static secrets or OAuth grants, with agent-owned secrets suited to shared services such as Tavily web search and user-owned OAuth enabling per-caller access to services such as GitHub, where actions and visible data reflect each user’s permissions and identity. Developers create connections with CLI commands, reference them in tools through `connections.get()` using a slug and owner type, and can rotate stored secrets without rebuilding deployments. OAuth support includes a catalog of providers requiring developers’ own app credentials, as well as MCP servers that self-register OAuth clients and expose tools directly, such as Linear. When users lack required grants, agent runs pause before model execution and present a consolidated authorization step, while token storage, refresh handling, callback routes, and consent-screen implementation are managed automatically. Local development supports agent credentials through environment variables and real user authorization under `mda dev`, while additional options support shared deployment OAuth accounts, scope restrictions, and custom OAuth providers.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
MCP 11 2,241 148 72 -74%
Secrets Management 1 451 99 43 -80%
Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.