How to Use the Pinterest Ads MCP in LlamaIndex

Build LlamaIndex RAG applications that index your Pinterest Ads performance data and query campaign metrics using natural language.

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Connect Pinterest Ads MCP to LlamaIndex

Create your Vinkius account to connect Pinterest Ads to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Pinterest Ads with LlamaIndex

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Index Pinterest Ads Performance into Your Knowledge Base

Stop relying on static spreadsheets to analyze your Pinterest Ads performance. By using this MCP Server, LlamaIndex can pull fresh data via `get_account_analytics` and `get_campaign_analytics`, converting raw JSON responses into searchable vector nodes. This allows your agent to answer complex questions about your ad spend by querying a live index. Instead of guessing, you get answers grounded in real-time metrics, completely eliminating the hallucination risks common in standard language models.

LlamaIndex Semantic Search Across Campaigns and Pins

Turn your Pinterest campaign structure into a queryable knowledge graph. Your LlamaIndex agent can call `list_campaigns` and `list_ads` to understand which creatives are currently active and how they map to your broader marketing goals. When you query your agent about which pins are driving the lowest cost-per-click, it searches the indexed outputs of `get_adgroup_analytics`. You get a direct, data-backed answer along with the exact campaign IDs responsible for those numbers.

Context-Aware Pinterest Campaign Control via MCP

Give your RAG pipelines the power to act on the insights they discover. When LlamaIndex identifies an underperforming ad group through semantic search, it can instantly call `pause_campaign` or `enable_campaign` to protect your budget. This closes the loop between data retrieval and action. Your agent doesn't just tell you that a campaign is failing; it uses the MCP toolset to fix the issue on Pinterest before you even log into your dashboard.

Setup guide

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

You connect to the Pinterest Ads MCP server using LlamaIndex's MCP tool spec integration. This turns tools like `list_campaigns` and `get_campaign_analytics` into data loaders that feed directly into your document indexes.

Yes, LlamaIndex can query historical metrics by pulling data through `get_account_analytics` and indexing the results over time. This lets you ask natural language questions comparing current performance to previous quarters.

LlamaIndex forces the agent to ground its answers in the actual JSON payloads returned by tools like `get_adgroup_analytics`. The agent reads the real-time data from the MCP Server rather than guessing.

Yes, you can use LlamaIndex's tool filtering options to restrict your agent's access. You can limit the tool list to only pull from specific campaigns when running `list_campaigns` or `list_adgroups`.

Your Pinterest ad group analytics and creative assets remain completely secure. The Vinkius MCP gateway handles authentication securely, passing data directly to your local LlamaIndex instance without storing your private marketing credentials or performance history.

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