MCP Sdlc Tracker
M

MCP Sdlc Tracker

An MCP server based on SQLite that provides complete software development lifecycle tracking functions, including epic, user story, task, defect, and test case management, and supports a Wiki documentation system, comment collaboration, and intelligent workflow suggestions.
2 points
7.0K

What is the SQLite MCP Tracker Server?

This is a project tracking and management tool specifically designed for software development teams. It provides a standardized interface through the Model Context Protocol (MCP), allowing AI assistants (such as Claude, Cursor, etc.) to help you manage the entire software development process. From requirement planning to test acceptance, all aspects can be managed through simple dialogue instructions.

How to use the SQLite MCP Tracker Server?

First, you need to connect the server to your AI assistant, and then manage the project through dialogue instructions. For example, you can tell the AI assistant to 'Create a user story' or 'List all ongoing tasks'. The server will automatically handle all technical details, including database management, status tracking, and dependency maintenance.

Use cases

Suitable for software development teams, project managers, product managers, and technical leaders. It is especially suitable for projects that require structured tracking of development progress, management of requirement changes, and coordination of multi - team collaboration. It can be flexibly adapted to both agile development and traditional waterfall models.

Main features

Complete SDLC management
Supports the management of the complete software development lifecycle from epics, user stories, tasks, defects to test cases. Each entity has clear state transitions and workflow rules.
Intelligent dependency management
Supports dependencies between epics, user stories, and tasks. The system will automatically check if dependencies are resolved and provide intelligent workflow suggestions.
Integrated Wiki system
The built - in Wiki documentation system supports Markdown format and can be linked to specific development entities. It is convenient for team knowledge management and documentation collaboration.
Intelligent workflow
Automated state transitions and intelligent suggestions. For example, when a task is completed, the system will suggest advancing the user story to the QA stage.
Comment collaboration system
All development entities support the comment function. Team members can discuss and provide feedback under specific items to maintain the context of communication.
Knowledge graph generation
Automatically analyzes project code and generates a visual knowledge graph to help understand the code structure, dependencies, and architectural design.
Web management interface
Provides an intuitive Web interface that displays all development entities in card form, supporting filtering, searching, and quick operations.
REST API support
In addition to the MCP protocol, it also provides a complete REST API, which is convenient for integration with other tools or development of custom front - ends.
Advantages
Out - of - the - box: No complex configuration is required, and it can be used after initialization.
AI - friendly: Complex operations can be completed through natural language instructions.
Lightweight: Based on SQLite, no additional database service is required.
Complete workflow: Covers the entire process from requirements to launch.
Flexible permission control: Different roles have clear operation permissions.
Real - time collaboration: Supports simultaneous operation and commenting by multiple users.
Data visualization: Provides clear dashboards and statistical views.
Easy to integrate: Supports multiple AI assistants and development tools.
Limitations
Requires AI assistant support: It is mainly designed to work with AI assistants.
Single - machine deployment: The SQLite database is suitable for small and medium - sized teams.
Learning curve: Basic software development terminology needs to be understood.
Network dependency: The Web interface requires local network access.
Customization limitations: Workflow rules are relatively fixed, and customization requires technical knowledge.

How to use

Installation and startup
First, install the Node.js environment, then clone or download the project code, install the dependencies, and start the server.
Connect to the AI assistant
According to the AI assistant you are using (Claude, Cursor, Windsurf, etc.), add the MCP server information to the configuration.
Initialize the database
Initialize the project database through the AI assistant or the Web interface, and specify the project directory path.
Start using
Now you can manage the project through natural language instructions. For example, create epics, user stories, tasks, etc.
Access the Web interface
After starting, access http://localhost:3000 to view the Web management interface and visually check the project status.

Usage examples

New project planning
The product manager needs to plan a new functional module, including multiple user stories and tasks.
Daily task management
The development team needs to assign and track the day's development tasks.
Defect tracking
The testing team discovers defects that need to be recorded and assigned.
Project documentation writing
The technical leader needs to write the system architecture documentation.
Progress tracking meeting
The project manager needs to prepare a progress report.

Frequently Asked Questions

What do I need to install to use this tool?
Which AI assistants are supported?
Where is the data stored? How can I back it up?
Can multiple users use it simultaneously?
How can I customize the workflow status?
Is there a difference between the functions of the Web interface and the AI assistant?
Does it support data import and export?
What should I do if I encounter the error 'Database not initialized'?
How can I upgrade to a new version?
Does it support mobile access?

Related resources

GitHub repository
Project source code and the latest version
MCP protocol documentation
Official documentation of the Model Context Protocol
SQLite documentation
Official documentation of the SQLite database
Example projects
Usage examples and best practices
Problem feedback
Submit problems and feature requests
Online demonstration
Online demonstration environment (read - only)

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "sdlc-tracker": {
      "command": "npm",
      "args": ["start"],
      "cwd": "/path/to/your/project"
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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