How to Use the Evoliz MCP in LlamaIndex

Q: How do I handle large catalogs of articles without hitting rate limits?

Use pagination with listarticles. This allows your agent to fetch articles in batches, indexing them step-by-step to prevent rate limit issues on the API.

Index your Evoliz invoices and client data directly into LlamaIndex vector stores for ground-truth RAG using this MCP Server.

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Connect Evoliz MCP to LlamaIndex

Create your Vinkius account to connect Evoliz 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 Evoliz with LlamaIndex

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Turn Evoliz MCP Server data into searchable knowledge

Stop guessing about past transactions. LlamaIndex indexes the outputs of `list_invoices` and `list_quotes` into your vector database, creating a searchable history of your French business operations. Your agent queries this index to find patterns without raw SQL. When you ask about specific billing histories, the agent pulls the exact records using `get_invoice`. This grounds your queries in real accounting data, preventing the LLM from hallucinating numbers that do not match your ledger.

Ground your financial queries in live client files

Keep your customer context accurate. Your LlamaIndex pipeline uses this MCP Server to run `list_clients` to ingest current customer profiles and indexes them for semantic search. When an agent needs to verify a billing address, it searches the index and retrieves the verified file via `get_client`. This eliminates manual data entry mistakes. If a customer changes their corporate structure, the agent runs `create_client` with the updated tax information, instantly refreshing the index so future queries use the correct data.

Direct retrieval of French catalog and pricing items

Feed your product catalog straight into your retrieval pipeline. By calling `list_articles` and `get_article` through the MCP Server, LlamaIndex indexes your services, prices, and tax rates. Your agent can then answer complex questions about product pricing based on current catalog files. This is highly useful for generating accurate quotes. The agent queries the article index, pulls the precise pricing, and compiles the quote using actual, compliant data stored in your account.

Setup guide

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

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Common questions about Evoliz MCP in LlamaIndex

Install llama-index-tools-mcp and initialize the client. You can then run `list_invoices` to pull your billing records and load them directly into your index using document parsers.

Yes, you can configure your agent to take action. When a query requires a new record, the LlamaIndex agent calls `get_quote` or updates files to keep your systems aligned.

It does. The agent can use semantic search to locate a customer profile in your index, then fetch the live, compliant record using `get_client` to verify VAT registration details.

Use pagination with `list_articles`. This allows your agent to fetch articles in batches, indexing them step-by-step to prevent rate limit issues on the API.

Nobody but you. Your invoice records and article lists are processed locally within your LlamaIndex pipeline, while the Vinkius sandbox ensures your API keys and credentials remain isolated and encrypted.

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