How to Use the Adtelligent MCP in LlamaIndex

Q: Can I filter Adtelligent results in LlamaIndex?

You can use the allowedtools filter to restrict which functions your agent calls. This helps keep your index focused on specific campaign subsets.

Index your Adtelligent campaign data into LlamaIndex for semantic search and grounded answers.

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Connect Adtelligent MCP to LlamaIndex

Create your Vinkius account to connect Adtelligent 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 Adtelligent with LlamaIndex

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LlamaIndex knowledge retrieval

Turn your `list_campaigns` results into a searchable knowledge base. LlamaIndex ingests the tool output and indexes it for fast semantic queries. Your agent no longer guesses campaign statuses. It searches the index to provide answers grounded in the actual data retrieved from your dashboard.

Query your advertiser records

Use `list_advertisers` to populate your vector store. You can then ask your agent questions about specific account history without re-running the tool. This method keeps your context window clean. It relies on the index to provide relevant details while keeping your API calls to a minimum.

Sync SSP reports to your index

Pull performance statistics via `get_ssp_report` and add them to your LlamaIndex pipeline. This creates a historical record of your ad revenue trends. Your RAG application benefits from structured API data. You get exact figures when you query your private knowledge base.

Setup guide

Set up Adtelligent 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 Adtelligent 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 Adtelligent tools.",
)
response = await agent.run("List recent Adtelligent 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 Adtelligent. 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 Adtelligent MCP in LlamaIndex

Use the MCP tool spec to wrap our endpoints. Once connected, your LlamaIndex agent can index the output from any of our three available tools.

Yes, the tool outputs are formatted for easy ingestion. You can pipeline the data directly into your vector storage engine.

You can use the allowed_tools filter to restrict which functions your agent calls. This helps keep your index focused on specific campaign subsets.

The connection remains active while your session is live. You can refresh your index as often as your rate limits allow.

We enforce strict transport security for all tool calls. Your SSP stats are processed in a transient sandbox and never written to permanent disk storage.

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