How to Use the CleverTap MCP in LlamaIndex

Q: Can I filter CleverTap results in LlamaIndex?

You can use allowedtools filters to restrict which data your agent pulls. It keeps your index clean and focused on the metrics that matter.

Build RAG pipelines in LlamaIndex that index your CleverTap engagement data for grounded answers.

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Connect CleverTap MCP to LlamaIndex

Create your Vinkius account to connect CleverTap 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 CleverTap with LlamaIndex

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Index CleverTap events in LlamaIndex

Use `list_event_schemas` to pull your custom events and feed them into a vector store. This turns your raw event logs into a searchable knowledge base. Your agent queries this index to find patterns in user behavior. It's how you get answers backed by real API data instead of guesses.

Query campaign history with LlamaIndex

Fetch historical performance using `list_clevertap_campaigns` and store the results in your index. You'll query past campaign success rates with natural language. It connects your historical marketing data to the current chat session. You'll find it useful for grounding your agent in the context of previous growth experiments.

Map user attributes for LlamaIndex RAG

Call `list_user_profile_properties` to build a metadata index of your user base. Your agent uses this index to filter search results based on specific user attributes. This makes your RAG application aware of your custom user data. It's a fast way to provide your agent with the specific details it needs to answer complex questions.

Setup guide

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

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Common questions about CleverTap MCP in LlamaIndex

You pull the API data through the server and pass it into your vector store. This makes your CleverTap metrics queryable by your agent.

You can use allowed_tools filters to restrict which data your agent pulls. It keeps your index clean and focused on the metrics that matter.

All traffic is handled through an endpoint token in our zero-trust sandbox. The CleverTap data is ephemeral and only exists where you direct it.

Yes, you convert the tools to a list and pass them directly to the agent. It integrates with the standard tool specification flow.

We isolate your user profile data within the V8 sandbox during every request. Your sensitive information is never stored beyond the active session.

Use it with your favorite AI tools

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