Mint MCP for AI. Controls AI agent access at the enterprise gateway level.

Listen up. Your LLMs are powerful, but they're also liabilities if you let them run wild against your core systems. You need a gatekeeper—a real one—to manage every single thing your AI agents touch. That's where the MintMCP server comes in. It runs as your centralized proxy layer, making sure that whether an agent reads data or tries to call a function, everything gets audited and checked for compliance first.

This isn't just logging; it's control.

When you need to restrict exactly what your agents can access, you use this server. You tell your AI client to route through MintMCP, and we handle the heavy lifting of governance and security guardrails across all your backend services. It acts as a virtual barrier that keeps everything contained.

Controlling Execution Scope

When an agent needs to perform an action, it doesn't talk directly to the source system; it talks to us. You can use mintmcp_run_tool_action to proxy and safely execute any logic stream that hits native integrations behind this gateway. This process keeps your sensitive systems completely insulated from the agent’s direct calls.

To figure out what services are even available for action, you start by looking at the abstraction layer. mintmcp_list_virtual_servers gives you a list of every proxy abstraction—these are functional groupings that bundle multiple tools together so your agents only see service names, not underlying complexity. If you need to know what specific functions fall under one of those abstractions, mintmcp_get_virtual_server extracts the exact configuration patterns for that unique Virtual Server schema.

Once you've got the list of services, you can drill down into what tools are approved inside a given server. You run mintmcp_list_available_tools, and it audits and returns every single underlying tool currently cleared for use within that specific virtual server. Crucially, you don't just get a name; you check the rules.

To know exactly who can execute what, you call mintmcp_get_tool_policy to retrieve the definitive SOC2 governance and Role-Based Access Control (RBAC) parameters for any single tool integration.

Enforcing Compliance and Redaction

We don't just track calls; we check the data itself. When an agent sends a payload, you run mintmcp_eval_guardrail. This function passes the structural parameter string through unified engines that explicitly check for PII redaction compliance. If the incoming text fails these standards—if it contains unredacted Personal Identifiable Information or violates other structural rules—the call dies immediately.

You don't get a warning; you get a hard stop.

Full Visibility and Shutting Down Threats

If something goes wrong, or if you just need to prove you’re compliant for an audit, we got your back. mintmcp_fetch_audit_logs dumps systematic telemetry logs, tracking every single access attempt against your entire SOC2 matrix and detailing all executions. You get a complete timeline of who tried to do what, and when.

And if you suspect a connection is compromised—if an agent’s session turns hostile or unauthorized—you don't wait for the damage report. You use mintmcp_revoke_access_token to immediately sever that runtime session by resolving any active OAuth flow or token, locking it out from the main host before it can cause trouble.

It’s a complete system: you see what services exist, you check if the agent has permission for those services, you verify the data is clean enough to pass, and if anything goes sideways, you kill the connection while documenting every step. You get total control over your AI environment.