What environment variables are required?
`SENDGRID_API_KEY`, `FROM_EMAIL`, and `OPENAI_MODEL` must be set in the `.env` file.
@MahithChigurupati
基本情報
Flex MCP Agent is an AI-powered agent designed to interface with MCP servers to process and resolve user queries. Simply configure it with MCP servers, and watch it scale effortlessly—no limits, no bottlenecks.
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": {
"Flex-MCP-Agent": {
"command": "python3",
"args": [
"-m",
"venv",
".venv"
]
}
}
}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。
An agent that integrates weather data retrieval, Confluence interaction, and email sending. It uses a structured chat agent and the Model Context Protocol (MCP) to standardize interactions between the agent and various data sources.
Clone the repository, create a virtual environment, install dependencies from requirements.txt, copy and update config.example.json to config.json and .env.example to .env with required keys, start the weather server (mcp_weather_server.py) and email server (mcp_email_server.py), then run mcp_agent.py.
`SENDGRID_API_KEY`, `FROM_EMAIL`, and `OPENAI_MODEL` must be set in the `.env` file.
Clone the separate Git repository referenced by the author for the Confluence MCP server.
Python packages: `langchain_mcp_adapters`, `langchain_openai`, `langchain`, `python-dotenv`, and `sendgrid`.
Yes, it uses a structured chat agent to interpret user input and decide which tool to call.
The configuration file `config.example.json` supports customizable URLs and transport methods, but specific transport types are not explicitly documented.

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