Uber Builds MCP Gateway to Govern Access to 800+ Servers and 5,000+ AI Agent Tools

8.4 relevance

Uber's MCP Gateway for AI agent tool governance is a perfect match for agent orchestration and platform engineering interests.

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Why It Matters

For a platform engineer focused on AI agent orchestration and cloud infrastructure, this demonstrates a production-grade pattern for governing multi-agent systems at scale, combining API gateway principles with LLM-specific concerns like PII redaction and incremental tool discovery.

Key Takeaways

Adopt a control-plane/data-plane separation for agent tool access, using automated discovery from existing IDL registries and incremental schema loading to avoid context-window bloat.

Uber Builds MCP Gateway to Govern Access to 800+ Servers and 5,000+ AI Agent Tools

Summary

Uber built an MCP Gateway to standardize AI agent access to over 800 servers and 5,000 internal tools, addressing fragmented integrations and inconsistent security. The architecture separates an MCP Registry (control plane) from a Proxy Gateway (runtime), translating MCP requests into HTTP, gRPC, or TChannel calls without modifying underlying services. AutoCrawler automates tool discovery via Cadence workflows, scanning Protocol Buffers and Thrift schemas, while Omni MCP supports incremental discovery to avoid loading all tool definitions into agent context.

Author

Leela Kumili