Ksawalakhe2024/Agentic_SDLC_Advance_Repo

Local Setup Guide: Minimal MCP Server for AI‑Powered Task Data Injection (with Podman)

This guide provides a step-by-step approach for running the MCP Server locally on your computer using Podman for PostgreSQL containerization and Spring Boot for the backend application.

1. Prerequisites

You’ll need:

• Java 17+ installed (java -version)
• Podman (for PostgreSQL container)
• Maven or Gradle (Install Maven)
• Git

1.1 Install Java 17+

Windows/Mac/Linux:

• Visit Adoptium Downloads and install Java 17 LTS for your platform.
• Verify installation:

  java -version
  

1.2 Install Podman

Windows:

• Download and install from the Podman Windows Installer.
• After installation, open a new terminal and run:

  podman --version
  

Mac:

• If Homebrew is installed:

  brew install podman
  

• Initialize Podman machine:

  podman machine init
  podman machine start
  

• Verify:

  podman --version
  

Linux (Ubuntu/Debian):

sudo apt-get -y update
sudo apt-get -y install podman
podman --version

Troubleshooting Podman

• If you see errors about the Podman machine, try podman machine start as needed.
• See Podman Getting Started for more.

1.3 Install Maven (if needed)

• Download from Maven Downloads and follow instructions for your OS.
• Verify:

  mvn -version
  

2. Clone the Repository

git clone https://github.com/Ksawalakhe2024/Agentic_SDLC_Advance_Repo.git
cd Agentic_SDLC_Advance_Repo

3. Start PostgreSQL with Podman

Run this command to start a local PostgreSQL instance:

podman run --name mcp-postgres \
  -e POSTGRES_PASSWORD=postgres \
  -e POSTGRES_DB=tasks_db \
  -p 5432:5432 \
  -d postgres:15

Check that the container is running:

podman ps

(Optional) Stop and remove the container:

podman stop mcp-postgres
podman rm mcp-postgres

4. Configure Application Properties

Edit src/main/resources/application.yml (create if missing):

spring:
  datasource:
    url: jdbc:postgresql://localhost:5432/tasks_db
    username: postgres
    password: postgres
  jpa:
    hibernate:
      ddl-auto: update
    open-in-view: false
    properties:
      hibernate.jdbc.time_zone: UTC
      hibernate.jdbc.batch_size: 100
      hibernate.order_inserts: true
      hibernate.order_updates: true
server:
  port: 8081
logging:
  level:
    root: INFO

5. Build the Project

If using Maven (with wrapper):

./mvnw clean install

Or, if Maven is installed globally:

mvn clean install

If using Gradle:

./gradlew build

6. Run the Spring Boot Application

Start with Maven:

./mvnw spring-boot:run

Or (if Maven installed globally):

mvn spring-boot:run

Or with Gradle:

./gradlew bootRun

The server should start on http://localhost:8081

7. Test Endpoints Manually

Check the API is running:

curl http://localhost:8081/mcp/help

Expected JSON output:

{
  "description": "MCP Task Data Gateway",
  "endpoints": [
    "/mcp/help",
    "/mcp/schema/tasks",
    "/mcp/tasks (POST)",
    "/mcp/tasks/summary"
  ]
}

8. Insert Sample Tasks

Create a test file (sample_tasks.json):

[
  {
    "title": "Test Task 1",
    "description": "First test task",
    "status": "NEW",
    "priority": 2,
    "dueDate": "2025-10-15T12:00:00Z"
  },
  {
    "title": "Test Task 2",
    "description": "Second test task",
    "status": "IN_PROGRESS",
    "priority": 1,
    "dueDate": "2025-10-20T09:00:00Z"
  }
]

Insert tasks using curl:

curl -X POST http://localhost:8081/mcp/tasks \
  -H "Content-Type: application/json" \
  --data-binary @sample_tasks.json

9. Get Summary

Check summary:

curl http://localhost:8081/mcp/tasks/summary

Expected output:

{
  "total": 2,
  "byStatus": {
    "NEW": 1,
    "IN_PROGRESS": 1,
    "DONE": 0,
    "BLOCKED": 0
  },
  "latestInsertedAt": "2025-09-18T09:30:11Z"
}

10. Stop Services

To stop PostgreSQL:

podman stop mcp-postgres

To remove the container (optional):

podman rm mcp-postgres

11. Troubleshooting

• If the app can’t connect to the DB, ensure the Podman container is running and port 5432 is open.
• If you get validation errors, check your JSON matches the schema (/mcp/schema/tasks).
• For logs, see the output in your terminal.

12. Evidence and Next Steps

• Insert 1,000 tasks in batches (split into files of ≤500 tasks each).
• Use /mcp/tasks/summary for confirmation.
• Document your results using the template in the main README.

You’re now ready to use the MCP server locally with Podman!