From e1ff1fb10ce65099ef10996ae84a4f5159377eb8 Mon Sep 17 00:00:00 2001
From: adk-bot <adk-bot@google.com>
Date: Thu, 9 Apr 2026 20:29:10 +0000
Subject: [PATCH] docs: Create agent-registry.md for new features

---
 docs/integrations/agent-registry.md | 85 +++++++++++++++++++++++++++++
 1 file changed, 85 insertions(+)
 create mode 100644 docs/integrations/agent-registry.md

diff --git a/docs/integrations/agent-registry.md b/docs/integrations/agent-registry.md
new file mode 100644
index 0000000000..533f0368e7
--- /dev/null
+++ b/docs/integrations/agent-registry.md
@@ -0,0 +1,85 @@
+# Google Cloud Agent Registry Integration
+
+The `AgentRegistry` client in the ADK provides a high-level interface for interacting with the Google Cloud Agent Registry service. This allows you to discover and integrate with registered agents and other resources within your Google Cloud project.
+
+## Initializing the AgentRegistry Client
+
+To get started, you need to initialize the `AgentRegistry` client with your Google Cloud project ID and location.
+
+```python
+from google.adk.integrations.agent_registry import AgentRegistry
+
+agent_registry = AgentRegistry(
+    project_id="your-gcp-project-id",
+    location="your-gcp-location",
+)
+```
+
+## Working with Endpoints
+
+The `AgentRegistry` client now includes methods for discovering and resolving model endpoints.
+
+### Listing Endpoints
+
+You can list all available endpoints in your configured project and location using the `list_endpoints()` method.
+
+```python
+all_endpoints = agent_registry.list_endpoints()
+print(all_endpoints)
+```
+
+### Getting a Specific Endpoint
+
+If you know the name of a specific endpoint, you can retrieve its details with the `get_endpoint()` method.
+
+```python
+endpoint_details = agent_registry.get_endpoint("projects/your-gcp-project-id/locations/your-gcp-location/endpoints/your-endpoint-id")
+print(endpoint_details)
+```
+
+### Resolving Model Names
+
+The `get_model_name()` method simplifies the process of extracting a model resource name from an endpoint.
+
+```python
+model_name = agent_registry.get_model_name("projects/your-gcp-project-id/locations/your-gcp-location/endpoints/your-endpoint-id")
+print(model_name)
+```
+
+## Authenticating MCP Toolsets
+
+When retrieving an MCP toolset with `get_mcp_toolset()`, you can now provide authentication details using the `auth_scheme` and `auth_credential` parameters. This allows the ADK to handle authentication when communicating with the MCP server.
+
+```python
+from google.adk.auth import AuthScheme
+from google.adk.auth.auth_credential import ServiceAccountCredential
+
+# Example using a service account for authentication
+auth_credential = ServiceAccountCredential(
+    service_account_email="your-service-account@your-project.iam.gserviceaccount.com"
+)
+
+mcp_toolset = agent_registry.get_mcp_toolset(
+    mcp_server_name="projects/your-gcp-project-id/locations/your-gcp-location/mcpServers/your-mcp-server",
+    auth_scheme=AuthScheme.GOOGLE_ID_TOKEN,
+    auth_credential=auth_credential
+)
+```
+
+## Custom HTTPX Client for Remote A2A Agents
+
+For advanced use cases, such as adding custom logging or telemetry, `get_remote_a2a_agent()` now supports injecting a custom `httpx.AsyncClient`.
+
+```python
+import httpx
+
+# Create a custom httpx client
+custom_client = httpx.AsyncClient(timeout=30.0)
+
+remote_agent = agent_registry.get_remote_a2a_agent(
+    agent_name="projects/your-gcp-project-id/locations/your-gcp-location/agents/your-agent-id",
+    httpx_client=custom_client
+)
+```
+
+This provides greater flexibility for controlling the HTTP communication between the ADK and the remote agent.