stavan30/af-log-bot-mcp
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The Artifactory Log Query Bot is a test project that simulates real-time Artifactory logs and allows querying them through a FastAPI-based MCP backend.
Artifactory Logs query Slack-bot. A test project. With MCP Server.
Artifactory Log Query Bot
This project simulates real-time Artifactory logs and allows querying them through a FastAPI-based MCP backend. It includes manual and natural language query support via CLI and Streamlit interfaces.
How to Run
-
Install dependencies
pip install -r requirements.txt -
Start the log simulator
python simulator/artifactory_log_simulator.py -
Start the MCP server
uvicorn app.main:app --reload -
Start the Streamlit chatbot interface
streamlit run chatbot_ui.py
Using Docker
To build and run the project using Docker:
-
Build the Docker image
docker build -t artifactory-log-bot .
-
Run the container
docker run -p 8000:8000 -p 8501:8501 artifactory-log-bot
The MCP API will be available at http://localhost:8000
The Streamlit UI will be available at http://localhost:8501
STEP1: MCP Server Setup
Created a FastAPI server with a /query endpoint.
It reads logs from a CSV file and filters them by:
- username
- response code
- keyword
- time window
STEP2: CLI Bot Integration
Created a CLI-based bot to interact with the MCP server.
Users enter filters manually, and the bot prints matching logs in the terminal.
STEP3: NLP-Based Query Parsing
Built an NLP parser to extract filters from natural language.
Integrated into the CLI bot so users can ask questions like:
"Show me 404 errors by john.wick in the last 10 minutes"
STEP4: Streamlit Chatbot Interface
Created a web interface using Streamlit.
Supports both manual filters and natural language queries.
Connects to the MCP server and displays logs in a chat-like view.