How to Use the Aidbase MCP in LlamaIndex

Q: Can LlamaIndex use Aidbase to handle support tickets?

It can certainly retrieve ticket details via getaidbaseinbox. The agent can then analyze these tickets and use the retrieved data to draft accurate replies.

Index your live support data into LlamaIndex for grounded answers using this Aidbase MCP Server.

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Connect Aidbase MCP to LlamaIndex

Create your Vinkius account to connect Aidbase 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 Aidbase with LlamaIndex

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Index Aidbase data in LlamaIndex

Turn your support history into a searchable vector index. The tools `list_aidbase_chatbots` and `list_aidbase_knowledge` pull raw data that LlamaIndex then embeds for semantic retrieval. This creates a grounded knowledge base that reflects your current support interactions. Your agent stops guessing and starts citing actual conversations.

Query live support context

Ask questions about your help desk metrics directly. Use the `get_aidbase_inbox` tool to grab ticket details which are then indexed alongside your documentation. This gives your agent a complete picture of past issues. It retrieves relevant past solutions from your inbox to inform current ticket responses.

Automate knowledge growth with MCP

Add new reference material to your index automatically. Use `add_aidbase_faq_item` to push updates into the system, which LlamaIndex then processes into your existing vector store. This creates a self-updating system. Your knowledge base grows as you add new FAQs, ensuring the agent always has the latest info.

Setup guide

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

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Common questions about Aidbase MCP in LlamaIndex

Use the McpToolSpec to fetch the tool list, then pass those to your LlamaIndex FunctionAgent. The agent will retrieve the data and store it in your vector index.

Yes, by calling the listing tools, the agent imports your knowledge into the index. You can then query it using natural language to find specific support documentation.

It can certainly retrieve ticket details via `get_aidbase_inbox`. The agent can then analyze these tickets and use the retrieved data to draft accurate replies.

The server provides an asynchronous interface for all tool operations. Use the async methods in your LlamaIndex setup to prevent blocking during data retrieval.

We isolate your support tickets and chatbot logs in a private sandbox. Only your authenticated LlamaIndex agent has access to the specific data objects retrieved during your query sessions.

Use it with your favorite AI tools

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