How to Use the LinkedIn Ads MCP in LlamaIndex

Q: Does LlamaIndex support filtering which LinkedIn Ads MCP tools are exposed?

Yes, you can use the allowedtools filter in LlamaIndex to only expose read-only tools like listadaccounts while keeping administrative tools hidden from the agent.

Index live LinkedIn Ads metrics directly into your LlamaIndex vector store using this MCP Server.

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Connect LinkedIn Ads MCP to LlamaIndex

Create your Vinkius account to connect LinkedIn Ads 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 LinkedIn Ads with LlamaIndex

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Perplexity

Semantic search over LinkedIn Ads campaigns with LlamaIndex

Stop searching through spreadsheets. Your LlamaIndex agent uses `list_ad_campaigns` and `list_campaign_groups` to pull your entire ad structure and index it directly into your local vector store. This lets you query your marketing setup using plain English. LlamaIndex searches the index to find which campaign groups contain active budgets, avoiding outdated information.

Grounding RAG in live analytics data

Hallucinations ruin report generation. By exposing `get_ad_analytics` to LlamaIndex as an MCP tool, your agent retrieves actual spend and click data before writing any summary. The LlamaIndex agent matches this live data with cached performance documents, ensuring every generated report is backed by real-time metrics instead of pre-trained guesses.

Indexing ad creatives and conversion rules

Keep your knowledge base updated by pulling ad assets with `list_ad_creatives` and mapping them against `list_conversion_rules`. LlamaIndex stores these relationships semantically. When you ask LlamaIndex which ad copy drove the most signups, the agent queries the vector store to connect the creative text with the active conversion tracking rules.

Setup guide

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

Use llama-index-tools-mcp to initialize the client, convert the tools with McpToolSpec, and let your query engine ingest the output of `list_ad_campaigns` into your index.

Yes. Instead of reading from a static index, you can configure `get_ad_analytics` as a live function tool so your LlamaIndex agent fetches the latest spend directly from the API during a chat.

Yes, you can use the allowed_tools filter in LlamaIndex to only expose read-only tools like `list_ad_accounts` while keeping administrative tools hidden from the agent.

The MCP Server handles the underlying API pagination, presenting clean lists of creatives or campaigns to LlamaIndex so your indexer doesn't run out of memory.

Your raw metrics and account structures are processed inside an ephemeral, zero-trust sandbox. LlamaIndex only receives the specific JSON outputs from `get_ad_analytics` that you explicitly request.

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