How to Use the Uniconta MCP in LlamaIndex

Q: Can I use Uniconta's inventory list in LlamaIndex?

Yes. You run listinventoryitems and index that result set. This allows you to build a system where users can ask complex, natural language questions about product availability or catalog codes.

Q: Does Uniconta support combining vendor and debtor data in LlamaIndex?

You absolutely can. By indexing the results of listcreditors (vendors) alongside listdebtors (customers), you create a unified knowledge base that answers questions about both sides of your business.

Index Uniconta ERP data for semantic search. Ground your AI answers in actual API results with LlamaIndex.

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Connect Uniconta MCP to LlamaIndex

Create your Vinkius account to connect Uniconta 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 Uniconta with LlamaIndex

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Creating a searchable knowledge base

Run `list_creditors` to pull all vendor records, then index the full list into your vector store. You can build an RAG application that lets users ask natural language questions like, 'What payment terms do we have with Vendor X?' The answer comes from searching the indexed API data, guaranteeing accuracy and eliminating hallucinations based on the actual output of `list_creditors`.

Deep financial query analysis

You can combine results from `list_daily_journals` with `list_gl_accounts`. Instead of just seeing a list, LlamaIndex indexes these records. A user can then ask: 'Show me all cash movements in Q3 that hit the expense account.' The system searches the combined index and provides the answer grounded in both journal entries and GL categories.

Customer and Employee Data Search

Need to find out details on a specific customer or employee? Use `get_debtor_details` or `list_employees`, index the resulting data, and then query it semantically. You can ask: 'What are the contact details for our largest debtor?' The system searches the indexed client and employee records to provide a direct, verifiable answer.

Setup guide

Set up Uniconta 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 Uniconta 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 Uniconta tools.",
)
response = await agent.run("List recent Uniconta data")

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Common questions about Uniconta MCP in LlamaIndex

LlamaIndex doesn't just call tools; it takes the output—like results from `list_debtors`—and turns them into a searchable index. This means your agent can answer questions based on the actual, indexed ERP data, not just general knowledge.

Yes. You run `list_inventory_items` and index that result set. This allows you to build a system where users can ask complex, natural language questions about product availability or catalog codes.

You absolutely can. By indexing the results of `list_creditors` (vendors) alongside `list_debtors` (customers), you create a unified knowledge base that answers questions about both sides of your business.

This MCP Server provides access to operational and financial records. The specific data types indexed include Vendor Information (from `list_creditors`), Customer Data (from `list_debtors`), and Product Catalog items (from `list_inventory_items`).

This server handles core financial and operational records. Specifically, it touches Account Records (from `list_gl_accounts`), Customer Data (from `list_debtors`), and Invoice Records (from `list_debtor_invoices`).

Use it with your favorite AI tools

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