Streaming Pipeline

Streamline your data processing with our robust pipeline. Easily ingest, process, and analyze real-time data using Docker containers for seamless deployment. Get started quickly with our simple setup instructions and start gaining insights from your data today.

Installation

Installing for Claude Desktop

Manual Configuration Required

This MCP server requires manual configuration. Run the command below to open your configuration file:

npx mcpbar@latest edit -c claude

This will open your configuration file where you can add the Streaming Pipeline MCP server manually.

Visit Streaming Pipeline

steps to start the services

  1. cd <path/to/streaming_pipeline>
  2. start rabbitmq and elasticsearch first by using command docker-compose up -d and wait until it starts On Terminal One:
  3. cd ./ingester
  4. run bash build.sh if linux/macos else run docker build -t ingester .
  5. run docker run -it --name ingester --network streaming_pipeline_default ingester:latest On Termial Two:
  6. cd ../produce_tweets
  7. run bash build.sh if linux/macos else run docker build -t produce_tweets .
  8. run docker run -it --name produce_tweets --network streaming_pipeline_default produce_tweets:latest

To get Counts:

  1. python get_counts.py - this is in the root folder
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Streaming Pipeline: MCP Server – MCP.Bar