How to Use the Pinecone MCP in OpenAI Agents SDK

Q: Can I use Pinecone to filter data in OpenAI Agents SDK?

Yes. Your agent uses queryvectors to find similar embeddings based on natural language input. It then processes that metadata within your agent's context.

Directly manage your vector indexes from OpenAI Agents SDK using native tools for querying, fetching, and monitoring.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Pinecone MCP to OpenAI Agents SDK

Create your Vinkius account to connect Pinecone to OpenAI Agents SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Pinecone with OpenAI Agents SDK

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Perplexity

Real-time index monitoring

Stop guessing your storage limits. Your agent uses `get_index_stats` to pull current vector counts and namespace distribution directly from the source. This data feeds into your OpenAI Agents SDK logic, allowing for automated scaling decisions before you hit write-limit errors.

Targeted vector retrieval

Pull specific records without scanning your entire index. Using `fetch_vectors`, your agent grabs exact IDs, ensuring your context window stays focused on relevant data. This keeps your OpenAI Agents SDK memory usage predictable and prevents the agent from hallucinating based on irrelevant vector noise.

Operational database control

Clean up your workspace using `delete_vectors` when old data expires. This MCP Server gives your agent the ability to prune indexes based on your own logic. Pair this with `list_indexes` to ensure your agent always points to the correct production environment during long-running tasks.

Setup guide

Set up Pinecone MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Pinecone tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Pinecone tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Pinecone tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Pinecone Agent",
            instructions="You have access to Pinecone tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Pinecone MCP in OpenAI Agents SDK

The server connects via HTTP, exposing all seven tools as native functions. Your agent discovers them automatically, letting you call them as standard Python methods.

Yes. Your agent uses `query_vectors` to find similar embeddings based on natural language input. It then processes that metadata within your agent's context.

Security is handled at the transport layer. We use V8 isolation for every request, ensuring your API keys never leak into the client execution environment.

The server returns a structured error. Your agent catches these exceptions immediately, allowing you to implement custom retry logic in your Python code.

Yes. This MCP Server only touches vector IDs, metadata, and index stats. It never moves your raw source files, keeping your sensitive information strictly within your infrastructure.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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