Energy Transition Intelligence

Name: Energy Transition Intelligence
Author: apifyforge

@apifyforge

Energy Transition Intelligence について

Energy transition intelligence for AI agents — this MCP server gives any LLM client access to 7 live data sources and 4 scoring models covering energy transition readiness, grid stress prediction, stranded asset risk, and EV infrastructure gap analysis.

基本情報

カテゴリ

その他

ライセンス

MIT

公開者

apifyforge

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "energy-transition-intelligence-mcp": {
      "url": "https://ryanclinton--energy-transition-intelligence-mcp.apify.actor/mcp"
    }
  }
}

ツール

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ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Energy Transition Intelligence?

An MCP server that gives any LLM client access to 7 live data sources and 4 scoring models covering energy transition readiness, grid stress prediction, stranded asset risk, and EV infrastructure gap analysis. Designed for energy investors, grid operators, climate finance teams, utility analysts, and EV infrastructure planners.

How to use Energy Transition Intelligence?

Add the server URL https://ryanclinton--energy-transition-intelligence-mcp.apify.actor/mcp to your MCP client (e.g., Claude Desktop, Cursor, Windsurf) using the provided JSON configuration. Then ask your AI client to run one of seven tools; the server dispatches parallel queries and returns structured JSON results.

Key features of Energy Transition Intelligence

4 quantified scoring models (Transition Readiness, Grid Stress, Stranded Asset Risk, EV Infrastructure Gap)
Composite transition grade (A-F) with weighted sub-scores
7 parallel data sources queried simultaneously per tool call
5-tier readiness and gap classifications (LAGGING to LEADER, ADEQUATE to DESERT)
Regulatory signal parsing from Federal Register with net support score
Standby mode deployment on Apify eliminates cold start latency
Spending limits enforced per tool call via Actor.charge()

Use cases of Energy Transition Intelligence

Energy investors compare transition readiness across candidate markets before committing capital.
Utility operators use grid stress prediction with 48-72 hour weather lookahead for dispatch planning.
ESG analysts quantify stranded asset exposure across fossil fuel holdings for portfolio reviews.
EV infrastructure developers identify underserved markets using charger density and EV adoption pressure.
Sustainability teams track carbon intensity and generation mix evolution for Scope 2 reporting.

FAQ from Energy Transition Intelligence

What tools are available and how much do they cost?

The server provides 7 tools: assess_transition_readiness, predict_grid_stress, evaluate_stranded_asset_risk, analyze_ev_infrastructure_gaps, track_carbon_trajectory, monitor_energy_regulation, and generate_energy_transition_brief. Each tool costs $0.045 per call.

How do I connect my MCP client to the server?

Add the following JSON to your MCP client configuration: {"mcpServers":{"energy-transition-intelligence-mcp":{"url":"https://ryanclinton--energy-transition-intelligence-mcp.apify.actor/mcp"}}}.

What data sources are included?

Seven sources: EIA Energy Data, UK Carbon Intensity API, Open Charge Map, FRED Economic Data, Weather Forecast API, Federal Register, and NSTA Oil & Gas Licenses.

How are the scoring models calculated?

Each model uses documented point allocations: Transition Readiness 0-100, Grid Stress 0-100, Stranded Asset Risk 0-100, and EV Infrastructure Gap 0-100. The composite grade weighs readiness 30%, inverted grid stress 20%, inverted stranded asset risk 25%, and inverted EV gap 25%.

Are there any runtime limits?

Spending limits are enforced per tool call using Actor.charge(), returning a clean error if the per-run budget is reached. The server runs in persistent Standby mode on Apify.