Enabling the Full Agent Registry Feature in Envo Proxy AI Gateway

[rohanakapoor]

Like to propose a full Agent Gateway service for the envoproxy AI-gateway

What is an AI Agent- Gateway

An Agent Gateway is a specialized control plane and network proxy designed for agentic AI workloads. Where traditional API Gateways manage HTTP/REST APIs for microservices, and AI/LLM Gateways route prompt tokens to LLMs, an Agent Gateway sits between AI agents, Model Context Protocol (MCP) servers, tool APIs, and other agents. It manages the stateful, session-based, and multi-step interactions inherent to autonomous agent systems

Why Is an Agent Gateway Needed?

As enterprises move from single LLM prompts to autonomous, multi-step agents that call tools and orchestrate workflows, major architecture and security problems arise:
Tool & MCP Sprawl: Agents need access to dozens of data stores, APIs, and tools. Wiring every agent directly to every tool creates a maintenance nightmare.
Identity & Delegation Risks: An agent acting on behalf of a user needs a way to pass permissions downstream (OAuth 2.1 / OIDC token exchange) without having hardcoded credentials or excessive access. Loop & Cost Control: Autonomous agents can enter infinite execution loops or make hundreds of recursive tool calls, causing runaway cloud and LLM costs.
Lack of Auditability: Standard HTTP logs don't capture multi-turn reasoning chains, tool execution arguments, or dynamic decision paths

Core Capabilities

|---------------------------------------------------------------------------
| Agent Gateway |
| +--------------------+ +--------------------+ +-------------------+ |
| | Identity & Auth | | Tool Discovery | | Token/Cost Control| |
| | (mTLS, OAuth 2.1) | | (MCP Server Reg) | | (Rate/Loop Limits)| |
| +--------------------+ +--------------------+ +-------------------+ |
| +--------------------+ +--------------------+ +-------------------+ |
| | Protocol Routing | | Safety Guardrails | | Full Tracing | |
| | (A2A, MCP, REST) | | (PII, Model Armor) | | (OTel/OpenInfr) | |
| +--------------------+ +--------------------+ +-------------------+ |
+-------------------------------------------------------------------------+
| | |
v v v
+---------------+ +---------------+ +---------------+
| LLM APIs | | MCP Tools | | Downstream |
| (OpenAI/Bedr) | | (Databases) | | Agents (A2A) |
+---------------+ +---------------+ +---------------+

MCP & Tool Management: Acts as an aggregator/multiplexer for Model Context Protocol (MCP) servers. It exposes tools to agents based on role-based access controls (RBAC).

Agent-to-Agent (A2A) Routing: Implements protocol standards so agents built in different frameworks (e.g., LangChain, CrewAI, Google ADK) can discover each other and communicate seamlessly.

Identity Propagation: Manages delegated access (e.g., via RFC 8693 token exchange), ensuring the agent carries the human user's identity and permissions when interacting with downstream microservices or tools.

Real-time Guardrails & Content Rules: Scans request payloads and tool execution arguments for prompt injections, data leakage, or unsafe execution patterns before forwarding traffic.

Agent-Aware Observability: Uses OpenTelemetry and GenAI semantic conventions to log entire multi-step agent reasoning chains, tool outputs, execution latency, and token consumption per agent/team.