Ember Climate MCP Server for AutoGen 11 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Ember Climate as an MCP tool provider through the Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="ember_climate_agent",
tools=tools,
system_message=(
"You help users with Ember Climate. "
"11 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* 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 Ember Climate MCP Server
Connect your AI agents to Ember Climate's open electricity dataset and gain instant access to global energy intelligence covering over 200 countries and regions.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Ember Climate tools. Connect 11 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Carbon Intensity Analysis — Track yearly and monthly carbon footprint (gCO2/kWh) of electricity grids worldwide
- Generation by Source — Break down electricity production by energy type: coal, gas, nuclear, wind, solar, hydro, and more
- Demand Trends — Analyze electricity consumption patterns in TWh with per-capita metrics across nations
- Power Sector Emissions — Monitor CO2 emissions from the power sector in megatonnes and percentage shares
- Renewable Capacity Tracking — Follow monthly wind and solar capacity installations in GW to measure clean energy deployment
- Multi-Country Comparison — Query multiple nations simultaneously using comma-separated country codes for comparative analysis
- Filter Discovery — Explore available entities, energy sources, and date ranges dynamically before making targeted queries
The Ember Climate MCP Server exposes 11 tools through the Vinkius. Connect it to AutoGen 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 Ember Climate to AutoGen via MCP
Follow these steps to integrate the Ember Climate MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 11 tools from Ember Climate automatically
Why Use AutoGen with the Ember Climate MCP Server
AutoGen provides unique advantages when paired with Ember Climate through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Ember Climate tools to solve complex tasks
Role-based architecture lets you assign Ember Climate tool access to specific agents — a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Ember Climate tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Ember Climate tool responses in an isolated environment
Ember Climate + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Ember Climate MCP Server delivers measurable value.
Collaborative analysis: one agent queries Ember Climate while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Ember Climate, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Ember Climate data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Ember Climate responses in a sandboxed execution environment
Ember Climate MCP Tools for AutoGen (11)
These 11 tools become available when you connect Ember Climate to AutoGen via MCP:
get_api_options
Use dataset (e.g., "electricity-generation"), temporal_resolution (e.g., "monthly", "yearly"), and filter_name (e.g., "entity", "series", "entity_code", "date", "year"). This tool is useful for discovering valid country codes, energy source types, and available date ranges before making specific data queries. Get available filter options for Ember electricity datasets
get_carbon_intensity_monthly
Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY-MM (e.g., "2023-01", "2024-12"). This helps analyze seasonal patterns in grid carbon footprint and track monthly decarbonization progress. Get monthly carbon intensity of electricity generation for countries/regions
get_carbon_intensity_yearly
Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY (e.g., "2020", "2023"). Returns emissions intensity data showing how clean or polluting the electricity grid is over time. Get yearly carbon intensity of electricity generation for countries/regions
get_electricity_demand_monthly
Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY-MM (e.g., "2023-01", "2024-12"). Useful for analyzing seasonal demand patterns, peak consumption periods, and demand forecasting. Get monthly electricity demand data for countries/regions
get_electricity_demand_yearly
Use entity or entity_code to specify countries (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY (e.g., "2020", "2023"). Essential for understanding energy consumption trends and comparing per-capita usage across nations. Get yearly electricity demand data for countries/regions
get_electricity_generation_monthly
). Returns generation in TWh and percentage share of total generation for each source. Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY-MM (e.g., "2023-01", "2024-12"). Use series to filter by specific energy sources (e.g., "coal", "wind", "solar", "hydro", "nuclear", "gas"). Perfect for analyzing seasonal generation patterns, renewable intermittency, and monthly energy mix changes. Get monthly electricity generation by source for countries/regions
get_electricity_generation_yearly
). Returns generation in TWh and percentage share of total generation for each source. Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY (e.g., "2020", "2023"). Use series to filter by specific energy sources (e.g., "coal", "wind", "solar", "hydro", "nuclear", "gas"). Essential for analyzing energy transition, renewable adoption, and fossil fuel phase-out progress. Get yearly electricity generation by source for countries/regions
get_generation_multi_entity
g., "BRA,DE,US" for Brazil, Germany, and United States). Use start_date and end_date with format YYYY for yearly or YYYY-MM for monthly data. Use series to filter by energy source (e.g., "coal", "wind", "solar", "hydro", "nuclear", "gas"). This is highly efficient for comparative analysis across multiple nations without making separate API calls. Example: entity_code="BRA,DE,US,CHN,IND" to compare BRICS+ nations energy generation. Get electricity generation data for multiple countries simultaneously
get_installed_capacity_monthly
Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY-MM (e.g., "2023-01", "2024-12"). Use series to filter by capacity type (e.g., "wind", "solar"). Tracks renewable infrastructure deployment and capacity growth over time across different nations. Get monthly installed power capacity (wind and solar) for countries
get_power_sector_emissions_monthly
Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY-MM (e.g., "2023-01", "2024-12"). Use series parameter to filter by emission types (e.g., "co2"). Enables granular tracking of monthly emission trends and seasonal variations in power sector pollution. Get monthly power sector CO2 emissions for countries/regions
get_power_sector_emissions_yearly
Use entity or entity_code to filter by country (e.g., "Brazil", "DE", "US"). Use start_date and end_date with format YYYY (e.g., "2020", "2023"). Use series parameter to filter by emission types (e.g., "co2"). Critical for tracking national decarbonization progress and climate policy effectiveness. Get yearly power sector CO2 emissions for countries/regions
Example Prompts for Ember Climate in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Ember Climate immediately.
"What is the carbon intensity of Brazil's electricity grid in recent years?"
"Compare wind and solar generation between Germany, China, and the US for the last 3 years."
"Show me the monthly electricity demand in France during 2024."
Troubleshooting Ember Climate MCP Server with AutoGen
Common issues when connecting Ember Climate to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Ember Climate + AutoGen FAQ
Common questions about integrating Ember Climate MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
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Connect Ember Climate to AutoGen
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.