How do I find my Atlas.so API Token?

Log in to your Atlas dashboard, go to **App Configuration > Data > API**, and you will find your API Token there.

Can I see help center articles via this server?

Yes, use the `list_articles` tool to retrieve a list of articles from your Atlas help center.

How are customer IDs handled?

Atlas uses unique internal IDs for customers. You can discover these IDs by using the `list_customers` tool or searching for a specific customer by email.

Atlas MCP Server for LlamaIndex 8 tools — connect in under 2 minutes

Name: Atlas
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Atlas as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Atlas. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Atlas?"
    )
    print(response)

asyncio.run(main())

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* 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 Atlas MCP Server

The Atlas MCP Server provides a seamless natural language interface to your Atlas.so customer support platform. Empower your AI agent to manage your entire support operation, from ticket auditing to customer oversight and knowledge base access.

LlamaIndex agents combine Atlas tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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.

Key Features

Ticket Management — List all active support tickets, retrieve detailed conversation metadata, and create new tickets directly from your chat.
Customer Oversight — Access and manage your customer database, including names, emails, and internal IDs.
Knowledge Base Access — List help center articles to provide accurate information based on your organization's documentation.
Team Monitoring — View a list of team users (agents) to understand your support capacity.
Real-time Support Analytics — Quickly audit active conversations and customer needs using simple natural language commands.
Secure API Integration — Uses your Atlas.so API Token for safe and authenticated access to your support data.

The Atlas MCP Server exposes 8 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 Atlas to LlamaIndex via MCP

Follow these steps to integrate the Atlas 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 8 tools from Atlas

Why Use LlamaIndex with the Atlas MCP Server

LlamaIndex provides unique advantages when paired with Atlas through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Atlas tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Atlas tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Atlas, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Atlas tools were called, what data was returned, and how it influenced the final answer

Atlas + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Atlas MCP Server delivers measurable value.

Hybrid search: combine Atlas real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Atlas 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 Atlas for fresh data

Analytical workflows: chain Atlas queries with LlamaIndex's data connectors to build multi-source analytical reports

Atlas MCP Tools for LlamaIndex (8)

These 8 tools become available when you connect Atlas to LlamaIndex via MCP:

create_ticket

Create a new support ticket

get_account_check

Verify Atlas account connection

get_customer

Get details for a specific customer

get_ticket

Get details for a specific ticket

list_articles

List help center articles

list_customers

List all customers in Atlas

list_tickets

List all support tickets in Atlas

list_users

List team users (agents)

Example Prompts for Atlas in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Atlas immediately.

"List all active support tickets in Atlas."

"Show me the details for ticket ID 'tick_12345'."

"Find all help articles related to 'Pricing'."

Troubleshooting Atlas MCP Server with LlamaIndex

Common issues when connecting Atlas to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Atlas + LlamaIndex FAQ

Common questions about integrating Atlas MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.