Treinta App MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Treinta App as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Treinta App. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Treinta App?"
)
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 Treinta App MCP Server
Connect your Treinta SMB store operator account directly to Vurb allowing Claude to perform deep digital bookkeeping natively.
LlamaIndex agents combine Treinta App tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through the 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
- Write Real Transactions — Easily ask to compute ''I sold two coffees for $10'' and watch it register into your daily accounting books seamlessly.
- Check Client Tab (Fiado) — Access the registered client list and rapidly probe who currently has an unpaid debt.
- Audit Inventory — Download your digital stock catalog reading precise shelf margins instantly.
- Macro Profit & Loss — Pull your dashboard KPIs asserting if your monthly operational balances ended green.
The Treinta App 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 Treinta App to LlamaIndex via MCP
Follow these steps to integrate the Treinta App 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 Treinta App
Why Use LlamaIndex with the Treinta App MCP Server
LlamaIndex provides unique advantages when paired with Treinta App through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Treinta App tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Treinta App tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Treinta App, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Treinta App tools were called, what data was returned, and how it influenced the final answer
Treinta App + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Treinta App MCP Server delivers measurable value.
Hybrid search: combine Treinta App real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Treinta App 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 Treinta App for fresh data
Analytical workflows: chain Treinta App queries with LlamaIndex's data connectors to build multi-source analytical reports
Treinta App MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Treinta App to LlamaIndex via MCP:
create_client
Register a new active client
create_product
Add a new store inventory product
create_transaction
Create a new business transaction
delete_transaction
Revert an incorrect transaction
get_business_stats
Get macro P&L operations dashboard
get_client
Fetch specific client debt profile
get_product
Fetch targeted product SKU details
list_clients
List registered customers/clients
list_products
Get complete business inventory
list_sales
List consolidated sales
list_transactions
List book flow transactions
update_product_stock
Update physical quantity of a product
Example Prompts for Treinta App in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Treinta App immediately.
"Audit the store today. Check recent logged transactions and summarize our business overall dashboard stats."
"Create a formal Income Transaction representing our $35 cash sale of the surplus store products."
"Delete this transaction id 123"
Troubleshooting Treinta App MCP Server with LlamaIndex
Common issues when connecting Treinta App to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTreinta App + LlamaIndex FAQ
Common questions about integrating Treinta App 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 Treinta App 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 Treinta App to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.