GitHub Copilot + Barndoor: Governed MCP Access | Barndoor
Govern GitHub Copilot's models, tools, and cost with Barndoor
Enable your team to use GitHub Copilot and build AI agents, governed by Barndoor so every tool, model, and token GitHub Copilot touches is scoped, approved, and logged.
How GitHub Copilot connects through Barndoor
Barndoor gives you one universal endpoint to your MCP servers for GitHub Copilot — connect once, use with all connected MCP servers and approved models.
- IT connects your tools at the org level. Authorize GitHub Copilot once in Barndoor.
- 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.
- Point GitHub Copilot at the Barndoor endpoint. One connection governs every tool, model, and agent action.
- Give your teams an approved catalog. Of the AI clients and models they’re approved to use.
Why govern GitHub Copilot with Barndoor
Barndoor is the AI Gateway, helping every business use AI and agents securely, reliably, and with control. It governs what GitHub Copilot can access, what it can do with that access, and which models it runs on.
No shadow AI. Every MCP server GitHub Copilot 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 GitHub Copilot makes is checked, scoped, and logged as it happens.
Model access. Control which models GitHub Copilot 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 GitHub Copilot connects to.
Full visibility. One audit-ready log of every MCP tool action and every model call GitHub Copilot makes.
Popular MCP servers to connect with GitHub Copilot
MCP
Atlassian
Project & Task Management
34 toolsBarndoor hosted](/content/integrations/atlassian/index.html)
MCP
Google Mail
Google Workspace
17 toolsBarndoor hosted](/content/integrations/google-mail/index.html)
MCP
Notion
File & Document Management
14 toolsOfficial Remote](/content/integrations/notion/index.html)
MCP
Salesforce
CRM, Sales & Marketing
69 toolsBarndoor hosted](/content/integrations/salesforce/index.html)
MCP
Slack
Communication & Collaboration
21 toolsBarndoor hosted](/content/integrations/slack/index.html)
MCP
Zoom
Communication & Collaboration
16 toolsBarndoor hosted](/content/integrations/zoom/index.html)
Frequently asked questions
Can I set different budgets for different teams or agents using GitHub Copilot?
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 GitHub Copilot usage.
How do I add a new MCP server for GitHub Copilot after initial setup?
IT or security adds the new MCP server to the approved catalog and sets its policy, and it becomes available to GitHub Copilot and every other connected AI client immediately, no per-client reconfiguration needed.
Why do I need an AI gateway if I already have GitHub Copilot?
GitHub Copilot 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 GitHub Copilot 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 GitHub Copilot itself deciding to allow or deny it.