PG&E Data Portals MCP Server for Google ADK 10 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add PG&E Data Portals as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.
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Vinkius supports streamable HTTP and SSE.
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
StreamableHTTPConnectionParams,
)
# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
connection_params=StreamableHTTPConnectionParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
)
)
agent = Agent(
model="gemini-2.5-pro",
name="pge_data_portals_agent",
instruction=(
"You help users interact with PG&E Data Portals "
"using 10 available tools."
),
tools=[mcp_tools],
)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About PG&E Data Portals MCP Server
Connect PG&E Data Portals to any AI agent and programmatically search, discover, and query PG&E's public energy datasets through natural conversation.
Google ADK natively supports PG&E Data Portals as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
What you can do
- Dataset Search — Search the complete PG&E Data Portals catalog for energy-related datasets
- Energy Usage — Query electricity and gas consumption data by ZIP code and date range
- EV Adoption — Access electric vehicle registration and adoption trends by geographic area
- Solar Generation — Retrieve solar energy production and net energy metering (NEM) statistics
- Energy Efficiency — Analyze program participation, energy savings achieved, and cost-effectiveness
- Grid Infrastructure — Access distribution circuit, substation, and grid capacity data
- Date Range Queries — Filter any dataset by specific time periods for trend analysis
- Dataset Metadata — Get schema information and field descriptions for all datasets
The PG&E Data Portals MCP Server exposes 10 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect PG&E Data Portals to Google ADK via MCP
Follow these steps to integrate the PG&E Data Portals MCP Server with Google ADK.
Install Google ADK
Run pip install google-adk
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Create the agent
Save the code above and integrate into your ADK workflow
Explore tools
The agent will discover 10 tools from PG&E Data Portals via MCP
Why Use Google ADK with the PG&E Data Portals MCP Server
Google ADK provides unique advantages when paired with PG&E Data Portals through the Model Context Protocol.
Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with PG&E Data Portals
Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
Seamless integration with Google Cloud services means you can combine PG&E Data Portals tools with BigQuery, Vertex AI, and Cloud Functions
PG&E Data Portals + Google ADK Use Cases
Practical scenarios where Google ADK combined with the PG&E Data Portals MCP Server delivers measurable value.
Enterprise data agents: ADK agents query PG&E Data Portals and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine PG&E Data Portals tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query PG&E Data Portals regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including PG&E Data Portals
PG&E Data Portals MCP Tools for Google ADK (10)
These 10 tools become available when you connect PG&E Data Portals to Google ADK via MCP:
get_dataset_schema
Use this to understand what columns and data types are available before querying. The datasetId is obtained from search_datasets or list_all_datasets. Get the schema/metadata for a specific PG&E dataset
list_all_datasets
Each dataset includes name, description, ID, and metadata. Use this as a starting point to explore what data is available from PG&E — includes energy usage, EV adoption, solar generation, energy efficiency programs, and grid infrastructure datasets. List all available datasets in the PG&E Data Portals catalog
query_by_date_range
Specify the dataset ID and start/end dates to retrieve records within that time period. Use this for time-series analysis across any dataset type. Dataset ID from search_datasets. Dates in YYYY-MM-DD format. This is useful for year-over-year comparisons and trend analysis. Query any PG&E dataset filtered by a specific date range
query_dataset
Optional filters can be passed as key-value pairs to narrow results (e.g., zip_code, year, region). Use this to retrieve actual data records from any dataset in the PG&E Data Portals. Dataset IDs are obtained from search_datasets or list_all_datasets. Query a specific PG&E dataset with optional filters
query_energy_efficiency
), and investment amounts. Use this to analyze program effectiveness and ROI of energy efficiency initiatives. Optional programType filters by program category. Year is YYYY format. Query PG&E energy efficiency program data
query_energy_usage
Returns electricity usage aggregated by customer segment (residential, commercial, industrial, agricultural). Use this to analyze energy consumption patterns in specific geographic areas over time. ZIP code format: 5-digit (e.g., "94102"). Dates in YYYY-MM-DD format. Query PG&E energy consumption data by ZIP code and date range
query_ev_adoption
Use this to analyze EV adoption trends, identify high-adoption areas, and correlate with charging infrastructure. ZIP code is 5-digit format. Year is YYYY format (e.g., "2024"). Query electric vehicle adoption data by ZIP code and year
query_grid_infrastructure
Use this to understand grid capacity, identify areas needing upgrades, or analyze reliability metrics. Region filters by geographic area. dataType can filter by specific infrastructure type. Query PG&E grid infrastructure and distribution data
query_solar_generation
Use this to analyze solar adoption and production trends. Region can be a county name or service area identifier. Year is YYYY format. Query solar energy generation data by region and year
search_datasets
Use this to discover available datasets before querying specific data. Returns dataset names, descriptions, IDs, and metadata. Optional query parameter filters results by keyword. Search the PG&E Data Portals catalog for energy datasets
Example Prompts for PG&E Data Portals in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with PG&E Data Portals immediately.
"List all available PG&E datasets."
"Show me electricity usage for ZIP code 94102."
"Show EV adoption trends by ZIP code for 2024."
Troubleshooting PG&E Data Portals MCP Server with Google ADK
Common issues when connecting PG&E Data Portals to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkPG&E Data Portals + Google ADK FAQ
Common questions about integrating PG&E Data Portals MCP Server with Google ADK.
How does Google ADK connect to MCP servers?
Can ADK agents use multiple MCP servers?
Which Gemini models work best with MCP tools?
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Connect PG&E Data Portals to Google ADK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.