Integrations
Provides a time API endpoint that returns the current timestamp, which the MCP agent can query when handling time-related questions
Connects to OpenRouter (an OpenAI-compatible API) to access language models for generating responses to user queries
Offers a chat interface for users to interact with the MCP agent, allowing them to ask time-related and general questions
time-mcp
A minimal agentic AI system that answers time-related and general questions using a tool-augmented LLM pipeline.
Features
- Flask API: Provides the current timestamp.
- MCP Agent Server: Reasoning agent that detects user intent, calls tools (like the time API), engineers prompts, and interacts with an LLM via OpenRouter (OpenAI-compatible API).
- Streamlit UI: Simple chat interface to talk to the AI agent.
Setup
1. Clone and Install Dependencies
2. Environment Variable
Set your OpenRouter API key (get one from https://openrouter.ai):
3. Run the Servers
Open three terminals (or use background processes):
Terminal 1: Flask Time API
Terminal 2: MCP Agent Server
Terminal 3: Streamlit UI
The Streamlit UI will open in your browser (default: http://localhost:8501)
Usage
- Ask the agent any question in the Streamlit UI.
- If you ask about the time (e.g., "What is the time?"), the agent will call the Flask API, fetch the current time, and craft a beautiful, natural response using the LLM.
- For other questions, the agent will answer using the LLM only.
Architecture
- The MCP agent detects intent, calls tools as needed, engineers prompts, and sends them to the LLM.
- Easily extensible to add more tools (just add to the MCPAgent class).
Customization
- Add more tools: Implement new methods in
MCPAgent
and updateself.tools
. - Improve intent detection: Extend
detect_intent()
inMCPAgent
. - Change LLM model: Update the
model
field incall_llm()
.
Requirements
- Python 3.7+
- See
requirements.txt
for dependencies.
Credits
- Built using Flask, Streamlit, OpenRouter, and Python.
- Inspired by agentic LLM design patterns.
This server cannot be installed
An agentic AI system that answers time-related questions by calling a time API tool and general questions using an LLM, accessible through a simple chat interface.
Related MCP Servers
- -securityFlicense-qualityProvides AI agents with comprehensive Twitter functionality through the Model Context Protocol standard, enabling reading tweets, posting content, managing interactions, and accessing timeline data with robust error handling.Last updated -41JavaScript
- -securityAlicense-qualityA lightweight, modular API service that provides useful tools like weather, date/time, calculator, search, email, and task management through a RESTful interface, designed for integration with AI agents and automated workflows.Last updated -PythonMIT License
- AsecurityAlicenseAqualityIntegrates with Harvest time tracking API, enabling AI assistants to manage time entries, projects, clients, and tasks through natural language commands.Last updated -112PythonMIT License
- -securityAlicense-qualityAn MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.Last updated -9JavaScriptApache 2.0