Tokens MCP

@antonkulaga

Tokens MCP について

MCP server for token metrics

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": {
    "tokens-mcp": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

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 Tokens MCP?

Tokens MCP is a Model Context Protocol server that provides a standardized interface for AI systems to access the Token Metrics API. It enables access to comprehensive cryptocurrency market data, backtesting trading strategies, generating visual performance metrics, analyzing token performance across timeframes, and building automated trading systems.

How to use Tokens MCP?

Install by cloning the repository and running uv sync. Configure your Token Metrics API key in a .env file and update the mcp_server_config.json file with the key and correct absolute path. Run the server with uv run mcp run run.py. For IDE use, Cursor natively supports MCP and will automatically detect the server when the project is opened.

Key features of Tokens MCP

Access comprehensive cryptocurrency market data
Implement and backtest trading strategies (e.g., moving average crossovers)
Generate visual performance metrics for strategies
Analyze token performance across different timeframes
Build automated trading systems with consistent API access
Integrates with IDEs supporting the Model Context Protocol

Use cases of Tokens MCP

Algorithmic trading bot development with crypto data access
Market research through token performance analysis
Strategy backtesting and visual performance evaluation
Automated trading systems with standardized API access

FAQ from Tokens MCP

What does Tokens MCP do?

It serves as an MCP server for the Token Metrics API, allowing AI systems to retrieve cryptocurrency market data, backtest strategies, and generate charts.

What are the dependencies and runtime requirements?

The project requires Python, uv for dependency management, and a Token Metrics API key. Configuration is done via .env and mcp_server_config.json.

How do I configure the API key?

Copy .env.example to .env and add your Token Metrics API key. Also update mcp_server_config.json with the key and the correct absolute path to the project directory.

How does it integrate with IDEs?

IDEs like Cursor that support the Model Context Protocol can automatically detect the server for direct AI interaction with the Token Metrics API.

Are there any known limitations?

The configuration file uses absolute paths that must be manually edited. Test files are manual scripts without assertions. Some Token Metrics API endpoints are implemented custom because they are unavailable in the existing library. The repository may contain experimental unused code.

よくある質問

What does Tokens MCP do?

It serves as an MCP server for the Token Metrics API, allowing AI systems to retrieve cryptocurrency market data, backtest strategies, and generate charts.

What are the dependencies and runtime requirements?

The project requires Python, `uv` for dependency management, and a Token Metrics API key. Configuration is done via `.env` and `mcp_server_config.json`.

How do I configure the API key?

Copy `.env.example` to `.env` and add your Token Metrics API key. Also update `mcp_server_config.json` with the key and the correct absolute path to the project directory.