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.

WCC Pinecone Integration

tri_angle/wcc-pinecone-integration

Crawl any website and store its content in your Pinecone vector database. Enhance the accuracy and reliability of your own AI Assistant with facts fetched from external sources or connect this integration to our Pinecone GPT Chatbot assistant available in Apify Store.

Tri⟁angle

145

3.9

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

4.7

Pinecone GPT Chatbot

tri_angle/pinecone-gpt-chatbot

Pinecone GPT Chatbot combines OpenAI's GPT models with Pinecone's database to generate insightful responses. Its interactive chatbot interface presents precise and comprehensive answers to user queries. Benefit from semantic understanding, efficient workflows, and enriched knowledge integration!

Tri⟁angle

4.6

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

176

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

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

JB Hi-Fi Scraper

mshopik/jb-hi-fi-scraper

Scrape JB Hi-Fi and extract data on tv and video equipment from jbhifi.com.au. Our JB Hi-Fi API lets you crawl product information and pricing. The saved data can be downloaded as HTML, JSON, CSV, Excel, and XML.

Mark Carter

Qdrant Integration

apify/qdrant-integration

Transfer data from Apify Actors to a Qdrant vector database.

Apify

4.5

ESPN NBA Scraper (Current Season Stats)

scraped/espn-nba-scraper-current-season-stats

This actor provides NBA player statistics sourced from ESPN, including performance data such as points, rebounds, assists, and more.

scraped

5.0

OpenSearch Integration

apify/opensearch-integration

Transfer data from Apify Actors to Amazon OpenSearch Service. This Actor is a good starting point for building question-answering systems, search functionality, or Retrieval-Augmented Generation (RAG) use cases.

Apify

4.4