How to Use the Lago MCP in LlamaIndex

Q: How do I load Lago tools into my LlamaIndex MCP setup?

Install llama-index-tools-mcp. Initialize BasicMCPClient and pass it to your tool spec.

Q: Can LlamaIndex filter which Lago tools my agent sees?

Yes. You use the allowedtools filter to restrict the agent to read-only operations like checking subscriptions.

Q: Does this support asynchronous tool calling?

You call await mcptoolspec.totoollistasync(). This keeps your RAG pipeline from blocking while fetching heavy invoice payloads.

Turn your billing history into a searchable RAG database. LlamaIndex queries Lago and indexes the results for semantic search.

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Setup Lago with LlamaIndex

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LlamaIndex MCP Server Integration

The `list_invoices` tool pulls your entire billing history so LlamaIndex can embed it into a vector store. Your knowledge worker asks a question about Q3 revenue, and the agent searches actual financial records instead of guessing. This setup turns static billing data into an active RAG application. You get answers grounded in real invoice totals, completely eliminating the risk of an LLM hallucinating a customer balance.

Semantic Plan Search

The `get_subscription` and `create_plan` tools give your LlamaIndex application direct read and write access to pricing structures. The agent pulls current subscription details, indexes them, and compares them against historical customer contracts. If a sales rep asks what a specific client pays, the system searches the indexed subscription data. It returns the exact rate limits and overage fees tied to that account.

Event Log Analysis

The `send_event` and `batch_events` tools let your application write new usage data while cross-referencing past behaviors. You pipe event logs into your vector database to track usage trends over time. When a customer disputes a bill, your agent searches the indexed event history to prove exactly when they triggered the charges. The MCP protocol handles the routing, so you never dig through raw database tables to find the discrepancy.

Setup guide

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

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Common questions about Lago MCP in LlamaIndex

Install `llama-index-tools-mcp`. Initialize `BasicMCPClient` and pass it to your tool spec.

Yes. You use the `allowed_tools` filter to restrict the agent to read-only operations like checking subscriptions.

Indexing turns raw JSON invoices into semantic text. Your team asks plain-English questions about revenue trends and gets mathematically accurate answers.

You call `await mcp_tool_spec.to_tool_list_async()`. This keeps your RAG pipeline from blocking while fetching heavy invoice payloads.

The server isolation ensures your raw plan configurations and external customer IDs never leak across sessions. The zero-trust MCP environment destroys the connection context immediately after the query completes.

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