You can access the Pinecone Integration programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/sse?actors=apify/pinecone-integration",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Pinecone Integration

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/sse?actors=apify/pinecone-integration along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=apify/pinecone-integration",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other MCP client of your choice.

If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.

Chroma Integration

apify/chroma-integration

This integration transfers data from Apify Actors to a Chroma and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.8

Weaviate Integration

apify/weaviate-integration

This integration transfers data from Apify Actors to a Weaviate and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.7

MCP Stress Tester

jakub.kopecky/mcp-stress-tester

A simple MCP Stress Tester client Actor for stress-testing your Model Context Protocol server. 💻⚡

Jakub Kopecký

Milvus Integration

apify/milvus-integration

This integration transfers data from Apify Actors to a Milvus/Zilliz database and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.5

Actors MCP Server

apify/actors-mcp-server

⚠️ Legacy: This Actor is outdated. For the latest features and full documentation, visit https://mcp.apify.com. Easily connect any Apify Actor to AI agents using Anthropic’s Model Context Protocol (MCP) with our actively maintained MCP server.

Apify

4.9

OpenAI Vector Store Integration

jiri.spilka/openai-vector-store-integration

The Apify OpenAI Vector Store integration uploads data from Apify Actors to the OpenAI Vector Store linked to OpenAI Assistant.

Jiří Spilka

180

4.8

Browserbase MCP Server

jakub.kopecky/browserbase-mcp-server

A Model Context Protocol (MCP) server that provides browser automation capabilities using Browserbase.

Jakub Kopecký

🎯 Instagram Ad Copywriter Creator

powerai/instagram-ad-copywriter-creator

Transform your Instagram marketing with AI-powered ad copy! This intelligent tool analyzes your product and target audience to generate compelling, conversion-focused Instagram ad content with professional headlines, persuasive body copy, and strategic CTAs.

PowerAI

5.0

ArXiv MCP server

jakub.kopecky/arxiv-mcp-server

The ArXiv MCP server provides a bridge between AI assistants and arXiv's research repository through the Model Context Protocol (MCP). It allows AI models to search for papers and access their content in a programmatic way.

Jakub Kopecký