Sprint MCP Server
Enables LLM agents to manage structured sprint-based development workflows following the Sprint Protocol, including sprint initialization, status checking, and manifest generation.
README
Sprint MCP Server
A combination agent workflow and MCP server focused around iterative, collaborative development between Humans and Agents.
Overview
This MCP server implements tools that support the Sprint Protocol defined in AGENTS.md. It enables LLM agents (like Claude) to manage structured sprint-based development workflows through the Model Context Protocol.
Features
- Sprint Management: Initialize, track, and complete sprints following the Sprint Protocol
- Status Checking: Verify active sprints and enforce single-sprint rule (S3)
- Manifest Generation: Automatically create sprint manifests with proper metadata
- Request Logging: Track all actions and decisions in request logs
- Protocol Enforcement: Validate sprint lifecycle rules and requirements
Installation
Prerequisites
- Node.js >= 18.0.0
- npm or yarn
Setup
- Clone this repository
- Install dependencies:
npm install
- Build the project:
npm run build
Usage
Running the Server
The MCP server communicates via stdio:
npm run dev
Or run the built version:
node dist/index.js
Connecting to Claude Desktop
Add this server to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"sprint-mcp": {
"command": "node",
"args": ["/path/to/sprint-mcp/dist/index.js"]
}
}
}
After restarting Claude Desktop, the sprint tools will be available.
Available Tools
start-sprint
Initialize a new sprint with manifest and directory structure.
Parameters:
title(string, required): Concise sprint titlegoal(string, required): Clear sprint objectiveowner(string, required): GitHub handle or name of sprint owner
Example:
{
"title": "Implement User Profile Service",
"goal": "Create microservice for user profile management with REST API",
"owner": "@johndoe"
}
Behavior:
- Checks for active sprints (rule S3)
- Generates unique sprint ID:
sprint-<number>-<hash> - Creates sprint directory in
planning/ - Generates
sprint-manifest.yamlandrequest-log.md - Suggests feature branch name
- Sets status to
planning
check-sprint-status
Verify current sprint state and check for active sprints.
Parameters: None
Returns:
- List of active sprints with details
- Count of completed sprints
- Warning if multiple active sprints detected (protocol violation)
- Confirmation if ready to start new sprint
Development
Build
npm run build
Watch Mode
npm run watch
Testing
npm test
Run tests in watch mode:
npm run test:watch
Generate coverage report:
npm run test:coverage
Project Structure
sprint-mcp/
├── src/
│ ├── index.ts # MCP server entry point
│ ├── common/
│ │ ├── logger.ts # Logging facade
│ │ └── file-utils.ts # File system utilities
│ ├── tools/
│ │ ├── start-sprint.ts # Start sprint tool implementation
│ │ └── check-sprint-status.ts # Status check tool
│ └── types/
│ └── sprint.ts # TypeScript type definitions
├── planning/ # Sprint artifacts directory
├── architecture.yaml # Canonical source of truth
├── AGENTS.md # Sprint Protocol definition
├── CLAUDE.md # Claude Code guidance
└── package.json
Sprint Protocol
This server implements the Sprint Protocol defined in AGENTS.md. Key principles:
- Precedence:
architecture.yaml>AGENTS.md> everything else - Sprint Control: Only one sprint active at a time (rule S3)
- Lifecycle: Plan → Approve → Implement → Validate → Verify → Publish → Retro → Learn
- Traceability: All actions logged in
request-log.md - Definition of Done: Code quality, testing, deployment, documentation, traceability
Logging
Logs are written to stderr to avoid interfering with MCP stdio protocol.
Set log level via environment variable:
LOG_LEVEL=debug node dist/index.js
Available levels: debug, info, warn, error
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.