How to Use the Pinterest Ads MCP in LlamaIndex

Q: How do I index Pinterest Ads campaigns into LlamaIndex?

You run the listpinterestcampaigns tool within a LlamaIndex data ingestion pipeline to convert campaign data into Document nodes. These nodes are then embedded and stored in your vector database for semantic search.

Q: Can LlamaIndex query Pinterest Ads analytics in real time?

Yes, by using the getpinterestanalytics tool as a query-time tool. When a user asks about recent performance, the LlamaIndex agent calls this tool to fetch live metrics instead of relying on outdated vector embeddings.

Q: Can I use LlamaIndex to search through Pinterest Ads keywords?

Yes, you can use listpinterestkeywords to retrieve active keywords and index them. This allows your LlamaIndex RAG system to identify keyword gaps by comparing search queries against active ad group targets.

Q: Does this MCP Server support LlamaIndex sub-question querying?

Yes, the server exposes discrete tools like listpinterestadgroups which LlamaIndex can break down into sub-questions. The agent can query multiple ad groups individually and synthesize a single performance report.

Q: How is my Pinterest Ads keyword data protected?

Your keyword lists fetched via listpinterestkeywords are processed entirely within the ephemeral Vinkius V8 sandbox. No data is stored on our servers, and your API credentials remain encrypted, keeping your targeting strategy completely private.

Index live Pinterest Ads campaign metrics directly into your LlamaIndex vector store using this MCP server.

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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 Campaigns for Semantic Search

The `list_pinterest_campaigns` tool extracts campaign structures so LlamaIndex can index them into your document store. This allows your agent to search through campaign objectives and budgets using natural language queries instead of database lookups. Once indexed, your RAG pipeline can instantly find campaigns matching specific product lines. You don't have to write custom SQL queries to filter your advertising data; you just ask your LlamaIndex agent for the relevant campaign.

Retrieve Audience Data with LlamaIndex RAG

The `list_pinterest_audiences` tool feeds target segment data directly into your LlamaIndex indexers using this MCP data connection. Your agent can cross-reference these active audiences with customer profiles stored in your local vector database. This grounding prevents your agent from hallucinating targeting options that do not exist on Pinterest. The agent checks the live index of active audiences before suggesting any budget reallocations or campaign updates.

Contextualize Board Performance via MCP Server

The `list_pinterest_boards` and `list_pinterest_pins` tools pull your organic creative structure directly into your LlamaIndex knowledge base. The agent uses this context to map which organic boards correlate with high-performing paid campaigns. By indexing this board data, your query engine can answer complex questions about creative distribution. You get a clear picture of how your organic pin taxonomy supports your paid advertising efforts.

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")

Get your connection token →

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 run the `list_pinterest_campaigns` tool within a LlamaIndex data ingestion pipeline to convert campaign data into Document nodes. These nodes are then embedded and stored in your vector database for semantic search.

Yes, by using the `get_pinterest_analytics` tool as a query-time tool. When a user asks about recent performance, the LlamaIndex agent calls this tool to fetch live metrics instead of relying on outdated vector embeddings.

Yes, you can use `list_pinterest_keywords` to retrieve active keywords and index them. This allows your LlamaIndex RAG system to identify keyword gaps by comparing search queries against active ad group targets.

Yes, the server exposes discrete tools like `list_pinterest_ad_groups` which LlamaIndex can break down into sub-questions. The agent can query multiple ad groups individually and synthesize a single performance report.

Your keyword lists fetched via `list_pinterest_keywords` are processed entirely within the ephemeral Vinkius V8 sandbox. No data is stored on our servers, and your API credentials remain encrypted, keeping your targeting strategy completely private.

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