How to Use the VivifyScrum MCP in LlamaIndex

Q: How does VivifyScrum help with querying project history using LlamaIndex?

You index the results of getworklogs. When you query, LlamaIndex searches this data to provide answers grounded in actual work records. It's reliable and specific.

Q: If I want to know about board structure using VivifyScrum and LlamaIndex, what do I index?

You should index the outputs from listboards and getboard. This allows you to query relationships—like finding all boards related to a specific team or organization.

Q: Can VivifyScrum provide configuration details for LlamaIndex?

Yes. You can call listwebhooks and index the result. Your agent can then answer questions like, 'What webhooks are currently configured?' based on real data.

Q: How do I use VivifyScrum to track current teams with LlamaIndex?

Call listteams and index that resulting list. Your agent can then search this knowledge base to answer questions about team membership or status months later.

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Connect VivifyScrum MCP to LlamaIndex

Create your Vinkius account to connect VivifyScrum to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup VivifyScrum with LlamaIndex

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Indexing project history

LlamaIndex can index the output from `get_worklogs`. You query past work logs, and the answer comes grounded in actual API data. This means you aren't relying on memory or guesses. Need to know who worked on what? Indexing these historical entries lets your agent search through months of activity using semantic queries.

Searchable project structures

The output from `list_boards` and `list_organizations` becomes part of a searchable knowledge base. You can ask, 'Which boards belong to the Acme Corp organization?' and get an indexed answer. This capability means you build applications where live API data and organizational structure combine into one queryable index.

Retrieving current item status

You can store the results of calling `get_item` or `list_board_items`. Later, when a user asks about a specific task, LlamaIndex retrieves the exact details and grounds the answer in that data. This is far better than generating a generic response. The system pulls concrete facts from the API call outputs.

Setup guide

Set up VivifyScrum MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all VivifyScrum MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to VivifyScrum tools.",
)
response = await agent.run("List recent VivifyScrum data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by VivifyScrum. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about VivifyScrum MCP in LlamaIndex

You index the results of `get_worklogs`. When you query, LlamaIndex searches this data to provide answers grounded in actual work records. It's reliable and specific.

You should index the outputs from `list_boards` and `get_board`. This allows you to query relationships—like finding all boards related to a specific team or organization.

Yes. You can call `list_webhooks` and index the result. Your agent can then answer questions like, 'What webhooks are currently configured?' based on real data.

This server touches project metadata and account details. The primary types include organization names, board IDs, and item descriptions retrieved via the MCP Server.

Call `list_teams` and index that resulting list. Your agent can then search this knowledge base to answer questions about team membership or status months later.

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