VivifyScrum MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Item, Get Account Info, Get Board, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add VivifyScrum as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The VivifyScrum app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 VivifyScrum. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in VivifyScrum?"
)
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 VivifyScrum MCP Server
Connect your VivifyScrum account to any AI agent and simplify how you manage your Scrum and Kanban workflows through natural conversation.
LlamaIndex agents combine VivifyScrum tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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.
What you can do
- Board Management — List all boards and organizations, and retrieve detailed configuration metadata for specific project spaces.
- Task Control — Create, list, and update items (tasks and stories) directly on your agile boards.
- Sprint Planning — List sprints for a board to track progress and plan future development cycles.
- Team Coordination — Query team lists and organization members to manage access and visibility.
- Operational Tracking — Monitor worklogs for time tracking and list configured webhooks for event monitoring.
The VivifyScrum MCP Server exposes 12 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.
All 12 VivifyScrum tools available for LlamaIndex
When LlamaIndex connects to VivifyScrum through Vinkius, your AI agent gets direct access to every tool listed below — spanning agile-methodology, scrum-boards, kanban-boards, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new task/story
Get account details
Get board details
Get item details
Get board worklogs
List items on a board
List all boards
List all organizations
List board sprints
List all teams
List configured webhooks
Update an item
Connect VivifyScrum to LlamaIndex via MCP
Follow these steps to wire VivifyScrum into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the VivifyScrum MCP Server
LlamaIndex provides unique advantages when paired with VivifyScrum through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine VivifyScrum tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain VivifyScrum tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query VivifyScrum, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what VivifyScrum tools were called, what data was returned, and how it influenced the final answer
VivifyScrum + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the VivifyScrum MCP Server delivers measurable value.
Hybrid search: combine VivifyScrum real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query VivifyScrum 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 VivifyScrum for fresh data
Analytical workflows: chain VivifyScrum queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for VivifyScrum in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with VivifyScrum immediately.
"List all boards in my VivifyScrum account."
"Show me the tasks for the 'Product Development' board."
"Create a new task named 'Verify API Scopes' on board '88231'."
Troubleshooting VivifyScrum MCP Server with LlamaIndex
Common issues when connecting VivifyScrum to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpVivifyScrum + LlamaIndex FAQ
Common questions about integrating VivifyScrum MCP Server with LlamaIndex.