Govern LangChain's models, tools, and cost with Barndoor

Enable your team to use LangChain and build AI agents, governed by Barndoor so every tool, model, and token LangChain touches is scoped, approved, and logged.

How LangChain connects through Barndoor

Barndoor gives you one universal endpoint to your MCP servers for LangChain — connect once, use with all connected MCP servers and approved models.

1. IT connects your tools at the org level. Authorize LangChain once in Barndoor.
2. IT or security define the policy. Which tools, people, and agents; what needs approval; what data is masked; what models are accessed; virtual keys, metering, token budgets.
3. Point LangChain at the Barndoor endpoint. One connection governs every tool, model, and agent action.
4. Give your teams an approved catalog. Of the AI clients and models they’re approved to use.

Why govern LangChain with Barndoor

Barndoor is the AI Gateway, helping every business use AI and agents securely, reliably, and with control. It governs what LangChain can access, what it can do with that access, and which models it runs on.

• No shadow AI. Every MCP server LangChain connects to is approved and provisioned by IT, not configured ad hoc.
• Centralized AI access. Which MCP servers, which tools, which people, which agents, what needs approval, is all defined once at the org level, so access never drifts person to person or agent to agent.
• Runtime enforcement. Every MCP tool call and model call LangChain makes is checked, scoped, and logged as it happens.
• Model access. Control which models LangChain can use through virtual keys, so it never holds raw provider credentials.
• Smart routing. Automatic failover waterfalls if a model or provider goes down.
• AI cost controls. Set spend limits and token budgets, and track usage across every model LangChain connects to.
• Full visibility. One audit-ready log of every MCP tool action and every model call LangChain makes.

Popular MCP servers to connect with LangChain

MCP Atlassian Project & Task Management](/content/integrations/atlassian/index.html)
MCP Google Mail Google Workspace](/content/integrations/google-mail/index.html)
MCP Notion File & Document Management](/content/integrations/notion/index.html)
MCP Salesforce CRM, Sales & Marketing](/content/integrations/salesforce/index.html)
MCP Slack Communication & Collaboration](/content/integrations/slack/index.html)
MCP Zoom Communication & Collaboration](/content/integrations/zoom/index.html)

Frequently asked questions

Can I set different budgets for different teams or agents using LangChain?
Yes. Token and spend budgets can be set per team, per user, or per individual agent, not just at the organization level. This is what lets you track and cap AI cost by who's actually driving it, whether that's a specific developer's agent or a whole department's LangChain usage.

How do I add a new MCP server for LangChain after initial setup?
IT or security adds the new MCP server to the approved catalog and sets its policy, and it becomes available to LangChain and every other connected AI client immediately, no per-client reconfiguration needed.

Why do I need an AI gateway if I already have LangChain?
LangChain handles the model interaction, but it doesn't enforce org-wide policy, cost limits, or audit logging on its own. That's what a gateway adds in front of it. Without one, every person or agent using LangChain is a separate, ungoverned point of access to whatever models and tools they can reach. An AI gateway makes that access centrally scoped, approved, and logged instead.

How does Barndoor protect against unapproved models or tools?
It blocks the request at the gateway before it reaches the model or tool, rather than LangChain itself deciding to allow or deny it.