Axonaut 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 Axonaut as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Axonaut. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Axonaut?"
)
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 Axonaut MCP Server
Transform your business administration with Axonaut, the all-in-one ERP designed for high-velocity teams. By connecting Axonaut to your AI agent, you turn complex organizational management into a natural conversation. Your agent can instantly audit unpaid invoices, list active quotations, manage CRM contacts, and orchestrate team tasks without you ever navigating through dense financial menus. Whether you're tracking expenses or preparing project reports, your agent acts as a direct bridge to your business data, ensuring your operations stay lean and efficient.
LlamaIndex agents combine Axonaut tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through 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
- CRM Orchestration — List and search through company and contact records to maintain a complete view of your business relationships.
- Financial Auditing — Retrieve and audit lists of invoices, quotations (quotes), and expenses directly through natural language.
- Task Management — Create, list, and manage team tasks with deadlines and descriptions to keep projects moving forward.
- Business Oversight — Explore your product catalog, active orders, and project milestones without manual dashboard data entry.
- Connectivity Check — Instantly verify your account health and retrieve current user context to ensure system integrity.
The Axonaut 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 Axonaut to LlamaIndex via MCP
Follow these steps to integrate the Axonaut 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 Axonaut
Why Use LlamaIndex with the Axonaut MCP Server
LlamaIndex provides unique advantages when paired with Axonaut through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Axonaut tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Axonaut tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Axonaut, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Axonaut tools were called, what data was returned, and how it influenced the final answer
Axonaut + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Axonaut MCP Server delivers measurable value.
Hybrid search: combine Axonaut real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Axonaut 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 Axonaut for fresh data
Analytical workflows: chain Axonaut queries with LlamaIndex's data connectors to build multi-source analytical reports
Axonaut MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Axonaut to LlamaIndex via MCP:
create_task
Create a new task
get_account_check
Verify Axonaut connection and get current user info
get_company
Get details for a specific company
list_companies
List all companies in Axonaut
list_contacts
List all contacts
list_expenses
List all expenses
list_invoices
List all invoices
list_orders
List all orders
list_products
List all products
list_projects
List all projects
list_quotations
List all quotations (quotes/devis)
list_tasks
List all tasks
Example Prompts for Axonaut in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Axonaut immediately.
"List all my invoices from the last 30 days."
"Create a task called 'Follow up with New Client' due tomorrow."
"Search for a company named 'TechCorp'."
Troubleshooting Axonaut MCP Server with LlamaIndex
Common issues when connecting Axonaut to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAxonaut + LlamaIndex FAQ
Common questions about integrating Axonaut 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 Axonaut 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 Axonaut to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.