Agile MCP Server

Transform Large Language Models into powerful agile project management assistants through the Model Context Protocol (MCP).

Overview

The Agile MCP Server provides a comprehensive set of tools for agile project management, including user story creation, sprint planning, progress tracking, and team coordination. It integrates seamlessly with MCP-compatible clients like Claude Desktop and Cursor to bring agile workflows directly into your development environment.

Related MCP server: Agile Planner MCP Server

Why Agile MCP?

• Empower LLMs: Turn your LLM into a proactive agile assistant, capable of managing projects, tracking progress, and guiding development workflows.

• Local & Private: All your project data is stored locally, ensuring privacy and control.

• Seamless Integration: Works with any MCP-compatible client, embedding agile practices directly into your existing development tools.

• Type-Safe & Robust: Built with Pydantic for robust data models and type-safe operations, ensuring reliability and maintainability.

Features

• User Story Management: Create, update, and track user stories with priorities, points, and tags

• Sprint Planning: Organize stories into time-boxed sprints with goals and timelines

• Progress Tracking: Monitor sprint progress, story completion, and team velocity

• MCP Integration: Works with any MCP-compatible client for seamless workflow integration

• Local Storage: All data stored locally in your project directory

• Type-Safe: Full TypeScript support with proper parameter validation

Quick Start

Installation

To get started with the Agile MCP Server, clone the repository and install dependencies:

git clone <repository-url>
cd agile_mcp
uv sync

Running the Server

You can run the server with your project directory:

uv run python -m agile_mcp --project .
uv run python -m agile_mcp --project .

# Or start without project (set later using tools)
uv run python -m agile_mcp

MCP Client Integration

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "agile-mcp": {
      "command": "uv",
      "args": ["run", "python", "-m", "agile_mcp", "--project", "/path/to/your/project"],
      "cwd": "/path/to/agile-mcp"
    }
  }
}

Documentation

• User Guide - Comprehensive guide for getting started and daily workflows

• API Reference - Complete documentation of all MCP tools and parameters

• Examples - Code examples and usage demonstrations

Available Tools

Project Management

• set_project - Set the project directory

• get_project - Get the current project directory

User Story Management

• create_story - Create a new user story

• get_story - Retrieve a story by ID

• update_story - Update an existing story

• list_stories - List stories with optional filtering

• delete_story - Delete a story

Sprint Management

• create_sprint - Create a new sprint

• get_sprint - Retrieve a sprint by ID

• list_sprints - List sprints with optional filtering

• update_sprint - Update an existing sprint

• manage_sprint_stories - Add/remove stories from sprints

• get_sprint_progress - Get detailed sprint progress

• get_active_sprint - Get the currently active sprint

Project Structure

agile_mcp/
├── src/agile_mcp/          # Main source code
│   ├── models/             # Data models (Story, Sprint, etc.)
│   ├── services/           # Business logic services
│   ├── storage/            # File system storage layer
│   ├── tools/              # MCP tool implementations
│   └── server.py           # Main MCP server
├── docs/                   # Documentation
│   ├── API_REFERENCE.md    # Complete API documentation
│   └── USER_GUIDE.md       # User guide and workflows
├── examples/               # Usage examples
├── tests/                  # Test suite
└── README.md               # This file

Development

Requirements

• Python 3.10+

• uv (for package management)

Setup Development Environment

# Install dependencies including dev tools
uv sync

# For development, you can also install the package in editable mode
# This allows you to run examples and tools without full path specifications
uv pip install -e .

# Run tests (includes coverage reporting by default)
uv run pytest

# Run tests with verbose coverage report
uv run pytest -v

# Run tests without coverage (for faster execution)
uv run pytest --no-cov

# Type checking
uv run mypy src/

# Code formatting
uv run ruff format src/ tests/
uv run ruff check src/ tests/

Running Examples

The example scripts demonstrate best practices for using the Agile MCP Server and can be run after setting up the development environment:

# Option 1: Using uv run (recommended for development)
uv run python examples/basic_usage_demo.py
uv run python examples/sprint_demo.py

# Option 2: After editable installation (alternative)
python examples/basic_usage_demo.py
python examples/sprint_demo.py

The examples demonstrate:

• basic_usage_demo.py: Core functionality including story creation, listing, and updates

• sprint_demo.py: Complete sprint workflow from creation to completion

Both examples use proper JSON parsing patterns that mirror how real MCP clients handle tool responses, making them excellent references for integration work.

Test Coverage

The project maintains a minimum test coverage of 75%. Coverage reports are automatically generated when running tests:

• Terminal Report: Shows missing lines for each file

• HTML Report: Detailed interactive report in htmlcov/ directory

• Coverage Threshold: Tests will fail if coverage drops below 75%

View the HTML coverage report by opening htmlcov/index.html in your browser after running tests.

Transport Options

The server supports multiple transport protocols:

# STDIO transport (default) - for direct LLM integration
uv run python -m agile_mcp --project . --transport stdio

# SSE transport - for web-based clients
uv run python -m agile_mcp --project . --transport sse --host 0.0.0.0 --port 8000

Project Directory Management

Start the server without a project directory and set it later using the set_project tool via your LLM client.

Examples

Basic Workflow

# 1. Set up project
set_project(project_path=".")

# 2. Create a user story
create_story(
    title="User Authentication",
    description="Implement secure login system",
    priority="high",
    tags="authentication, security"
)

# 3. Create a sprint
create_sprint(
    name="Sprint 1 - Foundation",
    goal="Establish core functionality",
    start_date="2025-01-07",
    end_date="2025-01-21"
)

# 4. Add story to sprint
manage_sprint_stories(
    sprint_id="SPRINT-123",
    action="add",
    story_id="STORY-456"
)

# 5. Start the sprint
update_sprint(sprint_id="SPRINT-123", status="active")

See the examples directory for more detailed usage examples.

Architecture

The Agile MCP Server follows a clean architecture pattern:

• Tools Layer: MCP-compatible tool interfaces

• Services Layer: Business logic and workflow management

• Storage Layer: File-based persistence with JSON storage

• Models Layer: Type-safe data models with Pydantic

All data is stored locally in a .agile directory within your project, ensuring full control and privacy of your project data.

Contributing

1. Fork the repository

2. Create a feature branch (git checkout -b feature/amazing-feature)

3. Make your changes following the coding standards

4. Add tests for new functionality

5. Ensure all tests pass (uv run pytest)

6. Commit your changes (git commit -m 'Add amazing feature')

7. Push to the branch (git push origin feature/amazing-feature)

8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built on the Model Context Protocol (MCP) standard

• Inspired by agile development practices and tools

• Uses FastMCP for MCP server implementation