GitScrum Sprints MCP Server
Plan and track sprints via GitScrum — manage sprint cycles, monitor KPIs, review burndown charts, and organize user stories and epics from any AI agent.
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What is the GitScrum MCP Server?
The GitScrum MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to GitScrum via 15 tools. Plan and track sprints via GitScrum — manage sprint cycles, monitor KPIs, review burndown charts, and organize user stories and epics from any AI agent. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (15)
Tools for your AI Agents to operate GitScrum
Ask your AI agent "What's the progress of our current sprint in the web-app project?" and get the answer without opening a single dashboard. With 15 tools connected to real GitScrum data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
GitScrum Sprints MCP Server capabilities
15 toolsList sprints across all workspaces
Create a new sprint
Create a user story
Get sprint details
Get task details by UUID
List epics in a project
List sprints in a project
Use the sprint_slug filter to see only tasks belonging to a specific sprint. Filter by status (todo, in-progress, done). List tasks in a project, optionally filtered by sprint
List user stories in a project
Get sprint KPIs
Get detailed sprint metrics
Get current sprint progress
Resource: burndown, burnup, performance, types, efforts, member_distribution, task, type_distribution. Get sprint reports with charts
Get sprint statistics
Update an existing sprint
What the GitScrum Sprints MCP Server unlocks
What you can do
- Sprint lifecycle — create, update, delete, and inspect sprints with precise date ranges and configurations
- Performance analytics — access sprint KPIs, detailed statistics, progress tracking, and velocity metrics in real-time
- Visual reports — retrieve burndown, burnup, performance, and distribution chart data for any sprint
- Backlog management — list and create user stories, browse epics, and view tasks filtered by sprint
- Cross-workspace visibility — list sprints across all workspaces for portfolio-level oversight
How it works
1. Subscribe to the GitScrum Sprints integration from the marketplace
2. Enter your GitScrum API token and company slug
3. Ask your agent to review sprint progress, analyze velocity trends, or plan the next iteration — works in Claude, Cursor, and any MCP client
Your agent delivers sprint analytics and agile insights without requiring manual dashboard navigation.
Who is this for?
- Scrum masters — review sprint KPIs and progress during standups and retrospectives
- Engineering managers — track velocity trends and team throughput across sprints
- Product owners — manage user stories and epics while monitoring delivery cadence
Frequently asked questions about the GitScrum Sprints MCP Server
Can my AI agent show me the burndown chart data for the current sprint?
Yes! Use sprint_reports with the resource set to 'burndown'. Your agent returns the ideal versus actual burn-down data points, so you can visualize or analyze sprint health instantly. You can also request 'burnup', 'performance', or 'member_distribution' reports.
Can I see what tasks are in a specific sprint?
Absolutely. Use list_tasks with the sprint_slug filter to see only tasks belonging to that sprint. You can further filter by status (todo, in-progress, done) to focus on what matters. Then use get_task to drill into any specific task for full details.
Does this integration support sprint velocity and metrics tracking?
Yes. Use sprint_metrics for detailed velocity, throughput, and efficiency data. Combined with sprint_kpis for high-level indicators and sprint_stats for task distribution analysis, you get a complete performance picture across any sprint.
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Connect GitScrum Sprints with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Give your AI agents the power of GitScrum MCP Server
Production-grade GitScrum Sprints MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.