How to Use the Gorgias MCP in LlamaIndex

Q: How do I register the Gorgias MCP Server tools in LlamaIndex?

Install llama-index-tools-mcp, initialize the BasicMCPClient with your Vinkius URL, and convert the tools using McpToolSpec. You then pass these tools directly to your FunctionAgent.

Q: Can LlamaIndex search for customers using Gorgias tools?

Yes. The agent calls listcustomers to search for profiles matching specific criteria. It can then use getcustomer to retrieve detailed contact information.

Q: How does LlamaIndex use this MCP Server for RAG?

The agent uses listtickets and listmessages to gather context for a user query. It injects this support data into the LLM prompt to generate an accurate, grounded answer.

Q: Can my agent create new support tickets?

Yes. The agent uses createticket to open new cases and createmessage to add the initial customer inquiry or internal notes.

Build RAG pipelines in LlamaIndex that index Gorgias support tickets and customer profiles using this MCP Server.

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Connect Gorgias MCP to LlamaIndex

Create your Vinkius account to connect Gorgias 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 Gorgias with LlamaIndex

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Index Gorgias support history into LlamaIndex vector stores

Your LlamaIndex agent calls `list_messages` and `list_tickets` to pull historical support data and index it directly into your vector database. This lets you run semantic search over past customer interactions to find how similar issues were resolved. Instead of querying the live API repeatedly, your agent searches the local index first. If it needs real-time data, it falls back to calling `get_ticket` to fetch the current state of an active ticket.

Ground customer responses in live Gorgias MCP Server data

Reading recent messages via `list_messages` and retrieving customer details with `get_customer` provides the live context your LlamaIndex RAG pipeline needs to prevent hallucinations. Your agent pulls these details before drafting a response. By combining indexed historical data with live tool outputs from `get_user`, your LlamaIndex agent writes replies that match your actual support policies. You then use `create_message` to send the accurate response back to the customer.

Automate customer profile updates based on query context

Your LlamaIndex agent updates records using `update_customer` after analyzing a customer's query history. The agent evaluates past tickets fetched via `list_tickets` and updates customer tags or notes to reflect their current status. This keeps your CRM data accurate without manual entry. The agent uses `get_customer` to read the current profile, determines what needs changing, and writes the updates back using `update_customer` in a single run.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Gorgias. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Gorgias MCP in LlamaIndex

Install `llama-index-tools-mcp`, initialize the `BasicMCPClient` with your Vinkius URL, and convert the tools using `McpToolSpec`. You then pass these tools directly to your `FunctionAgent`.

Yes. The agent calls `list_customers` to search for profiles matching specific criteria. It can then use `get_customer` to retrieve detailed contact information.

The agent uses `list_tickets` and `list_messages` to gather context for a user query. It injects this support data into the LLM prompt to generate an accurate, grounded answer.

Yes. The agent uses `create_ticket` to open new cases and `create_message` to add the initial customer inquiry or internal notes.

Vinkius hosts the MCP Server in an ephemeral, zero-trust sandbox. Your support tickets, customer profiles, and message threads are processed in-memory and never stored on Vinkius disks, keeping your customer data secure.

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