kardashev-mcp
MCP server for Kardashev Labs US grid data, giving agents live LMP, carbon intensity, load, curtailment, interconnection queues, ERCOT large loads, and the public RT-DA spread forecast track record. Requires no API key.
README
kardashev-mcp
MCP server for Kardashev Labs US grid data. Gives agents live LMP, carbon intensity, load, curtailment, interconnection queues, ERCOT large loads, and the public RT−DA spread forecast track record. No API key required.
Data comes from the public API at data.kardashevlabs.org.
Install
npx -y kardashev-mcp
Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"kardashev": {
"command": "npx",
"args": ["-y", "kardashev-mcp"]
}
}
}
Claude Code
claude mcp add kardashev -- npx -y kardashev-mcp
Tools
| Tool | What it returns |
|---|---|
list_isos |
Covered ISOs/RTOs and live ingest status |
get_fuel_mix |
Generation by fuel type (MW) |
get_carbon |
Carbon intensity (lbs CO₂/MWh) |
get_lmp |
Locational marginal prices (RT/DA) |
get_load |
Actual grid load (MW) |
get_load_forecast |
Near-term load forecast |
get_curtailment |
Solar/wind curtailment |
get_queue |
Interconnection queue projects |
get_large_load |
ERCOT large-load interconnection snapshot |
get_spread_forecast |
Live ERCOT RT−DA spread forecast (issued before delivery) |
get_forecast_track_record |
Scored public track record for the spread models |
Row-returning tools default to limit=50 (hard max 500) so agents stay within context budgets.
Optional env
| Variable | Default | Purpose |
|---|---|---|
KARDASHEV_BASE_URL |
https://data.kardashevlabs.org |
Override API base (local data plane) |
KARDASHEV_TIMEOUT_MS |
30000 |
Per-request timeout |
Develop
npm install
npm run build
npm start # stdio
npm run inspect # MCP Inspector
Links
- Website: kardashevlabs.org
- Forecast track record: kardashevlabs.org/forecast
- API docs: data.kardashevlabs.org/docs
- Python client:
kardashev - JS/TS client:
kardashev
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.