Bring Climate Data
to CrewAI
Create your Vinkius account to connect Ember Climate to CrewAI and start using all 11 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the 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.
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
How it works
- Subscribe to this server
- Enter your Ember Climate API Key (free, obtained via email signup)
- Start querying global electricity data from Claude, Cursor, or any MCP-compatible client
No more manual CSV downloads or spreadsheet wrangling. Your AI becomes an instant energy analyst, capable of answering complex questions about the global energy transition in seconds.
Who is this for?
- Climate Researchers — instantly retrieve emissions data and grid carbon intensity trends without writing data pipelines
- Energy Consultants — compare generation mixes across countries and track renewable adoption rates programmatically
- Sustainability Teams — monitor power sector decarbonization progress and contextualize corporate ESG goals against national benchmarks
- Policy Makers & Journalists — fact-check energy claims with authoritative data from over 200 geographies on demand
Built-in capabilities (11)
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
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
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
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
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
). 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
). 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
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
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
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
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
Why CrewAI?
When paired with CrewAI, Ember Climate becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Ember Climate tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Ember Climate in CrewAI
Why run Ember Climate with Vinkius?
The Ember Climate connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 11 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Ember Climate using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Ember Climate and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Ember Climate to CrewAI through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Ember Climate for CrewAI
Every request between CrewAI and Ember Climate is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
How do I get an Ember Climate API key and how long does it take?
Simply visit the Ember Climate API page, enter your email address, and click to request your key. You'll receive it via email almost instantly. It only takes 30 seconds — no OAuth apps to configure, no developer portals to navigate, no complex setup.
What countries and regions are covered by the Ember electricity dataset?
The dataset covers over 200 countries and geographical regions worldwide, including individual nations, continents (like Europe), and regional aggregates (like OECD, EU-27). You can use the get_api_options tool to discover all available entity codes and country names before querying specific data.
Can I compare electricity generation across multiple countries in a single query?
Yes! Use the get_generation_multi_entity tool and provide comma-separated ISO country codes in the entity_code parameter (e.g., "BRA,DE,US,CHN" for Brazil, Germany, USA, and China). This is highly efficient for comparative energy analysis without making multiple separate API calls.
What energy sources can I filter by when querying electricity generation?
You can filter by all major energy sources including fossil fuels (coal, gas, oil), renewables (wind, solar, hydro, bioenergy, geothermal), nuclear, and storage. Use the series parameter with values like "coal", "wind", "solar", "hydro", "nuclear", "gas". Call get_api_options with filter_name="series" to see the complete list of available energy types for any dataset.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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