How to Use the Jebbit MCP in LlamaIndex

Q: Does LlamaIndex support querying Jebbit reports?

Yes. You can use listreportingjobs to fetch recent report data and add it to your knowledge base for deeper analysis.

Index your Jebbit interactive content into LlamaIndex to build search-powered knowledge bases.

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Connect Jebbit MCP to LlamaIndex

Create your Vinkius account to connect Jebbit 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 Jebbit with LlamaIndex

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Index Jebbit content with LlamaIndex

Convert results from `list_experiences` into a searchable vector index. This allows you to query your past quiz structures and survey logic using natural language. It turns static platform data into an active knowledge base. Your application retrieves context from your actual experiences whenever it needs to answer questions.

Analyze zero-party data via LlamaIndex queries

Use `list_attributes` to pull consumer insights into your index. You can then perform semantic searches to find which attributes correlate with specific user behaviors. This makes your data queryable. Instead of digging through CSVs, you ask your application to find patterns across your captured survey responses.

Ground AI responses in Jebbit platform data

Connect `get_account` and `list_campaigns` to your agent to keep it informed about your current setup. The agent uses this real-time data to ground its outputs. It prevents hallucinations by using the MCP server as a source of truth. Your agent only reports on active campaigns and verified account settings.

Setup guide

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

Why Choose Vinkius

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Common questions about Jebbit MCP in LlamaIndex

Use the MCP tool spec to wrap the Jebbit client. This exposes the tool list to your agent, allowing for seamless indexing of API results.

Yes. You can use `list_reporting_jobs` to fetch recent report data and add it to your knowledge base for deeper analysis.

Absolutely. By indexing the output of your campaigns, you can quickly find which survey structures are generating the most engagement.

You choose the data. You index the specific API responses from the MCP server that you want your application to remember.

Your endpoint token strictly controls access. We only index the public-facing experience metadata and user-captured attributes that you explicitly request.

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