time-mcp
@suryawanshishantanu6
time-mcp について
MCP Server which returns current timestamp with streamlit app
基本情報
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": {
"time-mcp-suryawanshishantanu6": {
"command": "python",
"args": [
"flask_api.py"
]
}
}
}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 time-mcp?
time-mcp is a minimal agentic AI system that answers time-related and general questions using a tool-augmented LLM pipeline. It integrates a Flask API for the current timestamp, an MCP agent server for reasoning and tool calling, and a Streamlit chat interface.
How to use time-mcp?
Set the OPENROUTER_API_KEY environment variable, then run three components in separate terminals: python flask_api.py for the time API, python mcp_server.py for the MCP agent server, and streamlit run streamlit_ui.py for the UI. Open the Streamlit UI in your browser (default http://localhost:8501) and ask questions.
Key features of time-mcp
- Flask API provides the current timestamp.
- MCP agent server detects user intent and calls tools.
- Integrates with LLMs via OpenRouter (OpenAI-compatible API).
- Streamlit UI offers a simple chat interface.
- Easily extensible with additional tools via the MCPAgent class.
Use cases of time-mcp
- Ask for the current time and receive a natural language response.
- Ask general knowledge questions that are answered by the LLM.
- Demonstrate a tool-augmented agent pipeline for learning or prototyping.
FAQ from time-mcp
What dependencies are required to run time-mcp?
Python 3.7+ and the packages listed in requirements.txt. Also need an OpenRouter API key set as the OPENROUTER_API_KEY environment variable.
How does authentication work?
The system uses an OpenRouter API key for LLM access. The Flask time API does not require authentication.
Can I add more tools to the agent?
Yes. Implement new methods in the MCPAgent class and update self.tools. You can also improve intent detection by extending detect_intent().
What LLM model does time-mcp use?
The model is defined in the call_llm() method and can be changed by updating the model field. It uses OpenRouter, which provides access to various models.
Is there a web interface?
Yes, a Streamlit UI is provided. Run streamlit run streamlit_ui.py to open the chat interface in your browser.
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