Build, scan, sandbox, publish
Use source and behavioural checks before publishing a server to agents or employees.
Platform - MCP Gateway
Model Context Protocol gives agents real tools: files, databases, ticketing, CRM, cloud APIs and business systems. AI Warden gives platform teams a governed path to register, scan, approve, publish and observe governed MCP servers and tool calls.
MCP adoption journey
The goal is not to ban MCP. The goal is to make the approved path simple enough for developers and controlled enough for security.
For AI developers
Developers can bring an MCP server, test it, see why a tool call was blocked, and publish it to approved agents or users without writing bespoke gateway logic.
# example MCP registry entry server: jira-support-tools owner: devex-platform tier: production tools: - search_tickets - create_ticket - summarize_incident consumers: - it-support-agent - support-triage-pilot status: pending_security_review
For security teams
An MCP server can expose database reads, file access, email, ticket creation, customer records, cloud APIs or write actions. AI Warden applies familiar controls before agents get that power.
Gateway controls
AI Warden supports the practical reality of enterprise MCP adoption: some servers are built by your teams, some are already running, and some come from vendors.
Use source and behavioural checks before publishing a server to agents or employees.
Add owner, tier and data classification, then proxy calls through the gateway for scanning and logs.
Apply stricter DLP, egress and approval policy before agents can use vendor tools.
ICAP and scanner enforcement
MCP risk is not only which tool was called. It is what the model placed in the arguments and what the tool returned. AI Warden can inspect both sides with AI Warden rules and ICAP-supported DLP.
MCP evidence
AI Warden can record the user, agent, MCP server, method, arguments, response decision, scanner flags, ICAP result, latency, status and final outcome for governed tool calls.