GitScrum Sprints MCP Server for LlamaIndex 15 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GitScrum Sprints as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to GitScrum Sprints. "
"You have 15 tools available."
),
)
response = await agent.run(
"What tools are available in GitScrum Sprints?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About GitScrum Sprints MCP Server
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
LlamaIndex agents combine GitScrum Sprints tool responses with indexed documents for comprehensive, grounded answers. Connect 15 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
The GitScrum Sprints MCP Server exposes 15 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect GitScrum Sprints to LlamaIndex via MCP
Follow these steps to integrate the GitScrum Sprints MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 15 tools from GitScrum Sprints
Why Use LlamaIndex with the GitScrum Sprints MCP Server
LlamaIndex provides unique advantages when paired with GitScrum Sprints through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine GitScrum Sprints tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain GitScrum Sprints tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query GitScrum Sprints, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what GitScrum Sprints tools were called, what data was returned, and how it influenced the final answer
GitScrum Sprints + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the GitScrum Sprints MCP Server delivers measurable value.
Hybrid search: combine GitScrum Sprints real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query GitScrum Sprints to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying GitScrum Sprints for fresh data
Analytical workflows: chain GitScrum Sprints queries with LlamaIndex's data connectors to build multi-source analytical reports
GitScrum Sprints MCP Tools for LlamaIndex (15)
These 15 tools become available when you connect GitScrum Sprints to LlamaIndex via MCP:
all_sprints
List sprints across all workspaces
create_sprint
Create a new sprint
create_user_story
Create a user story
get_sprint
Get sprint details
get_task
Get task details by UUID
list_epics
List epics in a project
list_sprints
List sprints in a project
list_tasks
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
List user stories in a project
sprint_kpis
Get sprint KPIs
sprint_metrics
Get detailed sprint metrics
sprint_progress
Get current sprint progress
sprint_reports
Resource: burndown, burnup, performance, types, efforts, member_distribution, task, type_distribution. Get sprint reports with charts
sprint_stats
Get sprint statistics
update_sprint
Update an existing sprint
Example Prompts for GitScrum Sprints in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with GitScrum Sprints immediately.
"What's the progress of our current sprint in the web-app project?"
"Create a new sprint 'Sprint 15 — Payments' from April 14 to April 28."
"Show me the velocity metrics for the last completed sprint."
Troubleshooting GitScrum Sprints MCP Server with LlamaIndex
Common issues when connecting GitScrum Sprints to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGitScrum Sprints + LlamaIndex FAQ
Common questions about integrating GitScrum Sprints MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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.
Connect GitScrum Sprints to LlamaIndex
Get your token, paste the configuration, and start using 15 tools in under 2 minutes. No API key management needed.