How to Use the Axonaut MCP in LlamaIndex

Q: Does this MCP Server support data filtering?

You can use allowedtools filters to restrict which parts of your ERP the agent can access. This keeps your index focused on the data you actually need.

Build a searchable knowledge base from your ERP using LlamaIndex and this MCP Server.

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Connect Axonaut MCP to LlamaIndex

Create your Vinkius account to connect Axonaut 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 Axonaut with LlamaIndex

Ask AI about this MCP

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Claude

Perplexity

Index Axonaut data for RAG

Convert your `list_quotations` and `list_expenses` results into vector embeddings. You now query your historical financial data using natural language instead of searching manual logs. Your agent indexes these outputs to provide grounded answers. You stop guessing what happened last quarter and start querying your own business records.

Ground your agent with live API data

Use `list_companies` to feed your knowledge base with real-time firmographic information. LlamaIndex treats these tool results as primary sources for its reasoning engine. You build applications where the AI answers questions based on your actual business history. If a record isn't in your index, the agent knows exactly which tool to run to fetch the latest truth.

Unified search for ERP records

Combine your internal documents with the results of `list_products` to create a comprehensive query engine. Your agent retrieves data, indexes it, and synthesizes an answer. This approach turns your ERP into a searchable asset. You define the inclusion criteria and let the framework handle the heavy lifting of data retrieval.

Setup guide

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

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Common questions about Axonaut MCP in LlamaIndex

You use the McpToolSpec to retrieve data from the server and pass it directly into your indexing pipeline. The outputs are transformed into searchable embeddings immediately.

You install the MCP adapter, initialize the client, and convert tools to a list. From there, you add them to your FunctionAgent for immediate use.

Yes, once you list your contacts, the data is ingested into your vector store. You can then ask questions about specific clients or relationship histories.

You can use allowed_tools filters to restrict which parts of your ERP the agent can access. This keeps your index focused on the data you actually need.

Data is processed within a zero-trust sandbox. Your contact details are never stored in plain text and the connection terminates as soon as your session ends.

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