Can the agent create an invoice for a specific client?

Yes! Use `create_invoice` with the client UUID and line item details. The agent creates the invoice linked to the client account, including amounts, descriptions, and due dates. Use `list_clients` first to find the correct client UUID.

Can I monitor project budget health conversationally?

Absolutely. Use `project_budget` to get real-time budget consumption data, including remaining allocation and burn rate. Combine with `clientflow_dashboard` for the full revenue picture across all clients and projects.

What billing data can the agent access?

The agent can list and create clients, manage invoices (list and create), browse proposals, track time entries on tasks, and access the consolidated ClientFlow dashboard. All operations respect your GitScrum account permissions and organizational role.

GitScrum ClientFlow MCP Server for LlamaIndex 12 tools — connect in under 2 minutes

Name: GitScrum ClientFlow
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 12 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GitScrum ClientFlow 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 ClientFlow. "
            "You have 12 tools available."
        ),
    )

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

asyncio.run(main())

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* 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 ClientFlow MCP Server

What you can do

Client management — list, inspect, and create client records with contact details and project history
Invoice generation — create and review invoices linked to client accounts with line items and totals
Proposal drafting — browse existing proposals and their approval statuses for any client
Budget monitoring — check project budget consumption and remaining allocations in real-time
Dashboard insights — access the ClientFlow dashboard for a consolidated view of revenue and client activity
Time billing — list and log time entries on tasks for accurate client billing

LlamaIndex agents combine GitScrum ClientFlow 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.

The GitScrum ClientFlow 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.

How to Connect GitScrum ClientFlow to LlamaIndex via MCP

Follow these steps to integrate the GitScrum ClientFlow 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 12 tools from GitScrum ClientFlow

Why Use LlamaIndex with the GitScrum ClientFlow MCP Server

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

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

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

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

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

GitScrum ClientFlow + LlamaIndex Use Cases

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

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

Data enrichment: query GitScrum ClientFlow 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 ClientFlow for fresh data

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

GitScrum ClientFlow MCP Tools for LlamaIndex (12)

These 12 tools become available when you connect GitScrum ClientFlow to LlamaIndex via MCP:

clientflow_dashboard

Get ClientFlow dashboard overview

create_client

Create a new client

create_invoice

Pass additional fields as JSON in the body parameter. Create an invoice for a client

get_client

Get client details

get_invoice

Get invoice details

get_proposal

Get proposal details

list_clients

List all clients

list_invoices

List all invoices

list_proposals

List all proposals

list_time_entries

List time tracking entries

log_time

Log time on a task

project_budget

Get project budget

Example Prompts for GitScrum ClientFlow in LlamaIndex

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

"List all our clients on GitScrum."

"Show me the ClientFlow dashboard overview."

"Create a new client 'Acme Corp' with email billing@acme.com."

Troubleshooting GitScrum ClientFlow MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

GitScrum ClientFlow + LlamaIndex FAQ

Common questions about integrating GitScrum ClientFlow 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 ClientFlow tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.