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MCP EV Assistant Server

@Abiorh001

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

Abiorh001

MCP EV Assistant Server について

A powerful server implementation for managing Electric Vehicle (EV) charging stations, trip planning, and resource management. This server provides a comprehensive set of tools and APIs for EV-related services.

MCP EV Assistant Server の設定

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": {
    "mcp_ev_assistant_server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

MCP EV Assistant Server のツール

4

Find EV charging stations near a location

`address`: Location to search around (string, required)

Plan an EV-friendly route

`user_address`: Starting location (string, required)

概要

What is MCP EV Assistant Server?

MCP EV Assistant Server is a Python-based MCP server for managing Electric Vehicle (EV) charging stations, trip planning, and resource management. It provides tools and APIs for locating charging stations, planning EV-friendly routes, and handling EV-related PDF documents. It is intended for developers building EV assistant applications.

How to use MCP EV Assistant Server?

Clone the repository, set up a Python virtual environment, install dependencies with uv sync, and configure environment variables OPENCHARGE_MAP_API_KEY and GOOGLE_MAP_API_KEY in a .env file or servers_config.json. Start the server with python ev_assistant_server.py. Invoke tools like charge_points_locator and ev_trip_planner via an MCP client.

Key features of MCP EV Assistant Server

  • Locate EV charging stations by address, distance, and socket type
  • Plan EV-friendly routes with automatic charging stop integration
  • Consider vehicle range and current charge level
  • Manage PDF documents with automatic text extraction
  • Support resource subscriptions for real-time updates
  • Provide interactive prompts for charging and route planning

Use cases of MCP EV Assistant Server

  • Find nearby CCS or Type 2 charging stations in a city
  • Plan a road trip between two locations with optimal charging stops
  • Estimate charging time for a given vehicle model and charger power
  • Browse and extract text from EV user manuals stored as PDFs

よくある質問

1

What API keys are needed?

You need an OpenCharge Map API key and a Google Maps API key. Set them in the `.env` file or `servers_config.json`.

2

How do I configure the server?

Create a `.env` file with the two API keys, or add them to the `env` section of `servers_config.json`. The server expects a `Data/` directory for PDF resources.

3

Can I add custom tools or prompts?

Yes. Define the tool schema in `core.schemas`, implement the tool in `agentTools`, and register it in the tool handlers. Prompts are added in the `PROMPTS` dictionary with validation in `handle_get_prompt()`.

4

Where are PDF resources stored?

PDF files are placed in the `Data/` directory. The server automatically discovers them and supports text extraction with fallback methods.

5

What transport does the server use?

The server is an MCP server; the README shows tool calls via `client.call_tool`, indicating it follows the MCP protocol. Transport details are not explicitly stated, but the implementation implies standard MCP transport (e.g., stdio or HTTP).

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