Can my AI agent list all workspaces and drill into specific project details?

Absolutely. Use `list_workspaces` to browse all your organizational workspaces, then `list_projects` to see every project within a workspace. Your agent returns full metadata including member counts, settings, and creation dates — all without leaving your conversation.

I need to set up a new project with custom workflows and labels — can I do it all conversationally?

Yes. Tell your agent to create the project, then ask it to configure the workflow columns and create color-coded labels. The agent chains `create_project`, `list_workflows`, and `create_label` tools automatically to set up your board exactly as you describe it.

Does this integration let me modify or delete projects?

This core integration focuses on workspace exploration, project creation, and configuration management — including workflows and labels. For task-level operations like CRUD, subtasks, and checklists, use the dedicated GitScrum Tasks integration. All actions respect your GitScrum account permissions.

GitScrum MCP Server for LlamaIndex 16 tools — connect in under 2 minutes

Name: GitScrum
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 16 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GitScrum as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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. "
            "You have 16 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in GitScrum?"
    )
    print(response)

asyncio.run(main())

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About GitScrum MCP Server

What you can do

Browse workspaces — list all your organizational workspaces and retrieve details for each one
Manage projects — list, create, and inspect projects with full metadata including members and settings
Configure workflows — view and manage Kanban column definitions and workflow templates
Organize with labels — list, create, and update color-coded labels to categorize work
Access your profile — retrieve the authenticated user's profile across all workspaces

LlamaIndex agents combine GitScrum tool responses with indexed documents for comprehensive, grounded answers. Connect 16 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 MCP Server exposes 16 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 to LlamaIndex via MCP

Follow these steps to integrate the GitScrum 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 16 tools from GitScrum

Why Use LlamaIndex with the GitScrum MCP Server

LlamaIndex provides unique advantages when paired with GitScrum through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine GitScrum tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain GitScrum tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query GitScrum, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what GitScrum tools were called, what data was returned, and how it influenced the final answer

GitScrum + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the GitScrum MCP Server delivers measurable value.

Hybrid search: combine GitScrum real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query GitScrum 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 for fresh data

Analytical workflows: chain GitScrum queries with LlamaIndex's data connectors to build multi-source analytical reports

GitScrum MCP Tools for LlamaIndex (16)

These 16 tools become available when you connect GitScrum to LlamaIndex via MCP:

create_project

Create a new project

create_workspace

Create a new workspace

find_project

Find a project by name

get_me

Get authenticated user profile

get_project

Get project details

get_task

Get task details by UUID

get_workspace

Get workspace details

list_labels

List labels in a project

list_project_members

List members in a project

list_projects

List projects in a workspace

list_tasks

Filter by status (todo, in-progress, done). Essential for understanding project scope and workload. List tasks in a project

list_workflows

List workflows (columns) in a project

list_workspaces

List all GitScrum workspaces

my_role

Get my role in the workspace

project_stats

Get project statistics

workspace_stats

Get workspace statistics

Example Prompts for GitScrum in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with GitScrum immediately.

"Show me all the workspaces I have access to on GitScrum."

"Create a new project called 'Mobile App v2' in the acme-eng workspace with a description."

"What labels are available in the web-app project?"

Troubleshooting GitScrum MCP Server with LlamaIndex

Common issues when connecting GitScrum to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

GitScrum + LlamaIndex FAQ

Common questions about integrating GitScrum MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query GitScrum tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.