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Github MCP Server

@dre1144

リポジトリ

基本情報

カテゴリ

金融とコマース

トランスポート

stdio

作者

dre1144

投稿者

Andrey

Github MCP Server について

概要はまだありません

#finance#portfolio-analysis#recommendation-agent

Github MCP 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": {
    "github": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SUPABASE_URL",
        "-e",
        "SUPABASE_SERVICE_KEY",
        "-e",
        "ENCRYPTION_KEY",
        "-e",
        "MCP_API_KEY",
        "-e",
        "MCP_API_URL",
        "-e",
        "GITHUB_PERSONAL_ACCESS_TOKEN",
        "mcp/finance-portfolio-agent"
      ],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
      }
    }
  }
}

Github MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

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 MCP Finance Agent?

MCP Finance Agent is a Model Context Protocol agent for analyzing financial portfolios and generating recommendations. It integrates with the Tinkoff Invest API to provide portfolio analysis, risk assessment, and optimization suggestions.

How to use MCP Finance Agent?

Clone the repository, install dependencies with Poetry, configure environment variables in a .env file, then run the agent using poetry run python -m src.main. The API becomes available at http://localhost:8000.

Key features of MCP Finance Agent

  • Integration with Tinkoff Invest API
  • Portfolio and risk analysis
  • Recommendation generation for portfolio optimization
  • Real-time market data monitoring
  • Efficiency metric calculations

Use cases of MCP Finance Agent

  • Automated portfolio risk assessment
  • Personalized portfolio rebalancing recommendations
  • Continuous monitoring of financial positions

よくある質問

1

What runtime does MCP Finance Agent require?

Python 3.11+ and Poetry for dependency management are required.

2

How do I configure MCP Finance Agent?

Create a `.env` file based on `.env.example` and set the required environment variables (e.g., API keys for Tinkoff Invest).

3

How is the agent tested?

Run `pytest` to execute all tests with coverage reporting. Specific tests can be run individually, and tests can be filtered by marker (e.g., `-m "not integration"`).

4

What is the structure of the project?

Source code lives in `src/` with subdirectories for the agent core, external services, and data models. Tests are in `tests/` and documentation in `docs/`.

5

How do I start development?

Activate the virtual environment with `poetry shell`, install pre-commit hooks with `pre-commit install`, and run tests with `pytest`.

コメント

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