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": {
        "local-actors-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "@apify/actors-mcp-server",
                "--actors",
                "apify/pinecone-integration"
            ],
            "env": {
                "APIFY_TOKEN": "<YOUR_API_TOKEN>"
            }
        }
    }
}

Configure MCP server with Pinecone Integration

You can interact with the MCP server via standard input/output - stdio (as shown above), which is ideal for local integrations and command-line tools such as the Claude desktop client, or you can interact with the server through Server-Sent Events (SSE) to send messages and receive responses, which looks as follows:

{
    "mcpServers": {
        "remote-actors-mcp-server": {
            "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 supported 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

4.7

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

139

3.9

Qdrant Integration

apify/qdrant-integration

Transfer data from Apify Actors to a Qdrant vector database.

Apify

4.5

PGVector Integration

apify/pgvector-integration

This integration transfers data from Apify Actors to a Postgres SQL database (with PGVector extension).

Apify

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

165

4.8

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

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

Actor Builder

useful-tools/actor-builder

Simple Actor which allows to create another Actors build. Used mostly for integration purposes.

Useful tools

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