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wehub-resource-sync
2026-07-13 13:25:13 +08:00
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# BigQuery API Registry Agent
This agent demonstrates how to use `ApiRegistry` to discover and interact with Google Cloud services like BigQuery via tools exposed by an MCP server registered in an API Registry.
## Prerequisites
- A Google Cloud project with the API Registry API enabled.
- An MCP server exposing BigQuery tools registered in API Registry.
## Configuration & Running
1. **Configure:** Edit `agent.py` and replace `your-google-cloud-project-id` and `your-mcp-server-name` with your Google Cloud Project ID and the name of your registered MCP server.
1. **Run in CLI:**
```bash
adk run contributing/samples/api_registry_agent -- --log-level DEBUG
```
1. **Run in Web UI:**
```bash
adk web contributing/samples/
```
Navigate to `http://127.0.0.1:8080` and select the `api_registry_agent` agent.
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# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from . import agent
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# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from google.adk.agents.llm_agent import LlmAgent
from google.adk.integrations.api_registry import ApiRegistry
# TODO: Fill in with your GCloud project id and MCP server name
PROJECT_ID = "your-google-cloud-project-id"
MCP_SERVER_NAME = "your-mcp-server-name"
api_registry = ApiRegistry(PROJECT_ID)
registry_tools = api_registry.get_toolset(
mcp_server_name=MCP_SERVER_NAME,
)
root_agent = LlmAgent(
name="bigquery_assistant",
instruction=f"""
You are a helpful data analyst assistant with access to BigQuery. The project ID is: {PROJECT_ID}
When users ask about data:
- Use the project ID {PROJECT_ID} when calling BigQuery tools.
- First, explore available datasets and tables to understand what data exists.
- Check table schemas to understand the structure before querying.
- Write clear, efficient SQL queries to answer their questions.
- Explain your findings in simple, non-technical language.
Mandatory Requirements:
- Always use the BigQuery tools to fetch real data rather than making assumptions.
- For all BigQuery operations, use project_id: {PROJECT_ID}.
""",
tools=[registry_tools],
)