Webhook → AI → Pinecone & Qdrant
- 1
Trigger
Webhook trigger receives data from your app or form.
- 2
AI Agent
Write or transform the content with your instructions.
- 3
Vector Database
Run the Pinecone & Qdrant action you configure on the node.
Your own vector database for semantic search.
What the Pinecone & Qdrant integration supports today, and where it shows up in the product.
vector_store[ API key ]
Add your Pinecone & Qdrant credentials (api key) in Connections, then use them from workflows and the agent.
Starting points you can build in the Workflow Builder or ask the agent for. Each step is a real node or tool.
Trigger
Webhook trigger receives data from your app or form.
AI Agent
Write or transform the content with your instructions.
Vector Database
Run the Pinecone & Qdrant action you configure on the node.
Schedule Trigger
Run on a schedule while the workflow is active.
AI Agent
Generate the content or decision for this run.
Vector Database
Hand the result to Pinecone & Qdrant.
AI chat
Describe what you want done in Pinecone & Qdrant in plain language.
vector_store tool
The agent calls its Pinecone & Qdrant tool on your connected account.
Add your Pinecone & Qdrant credentials (api key) in Connections, then use them from workflows and the agent.
Index, query and delete vectors; Semantic search in workflows and the agent. You use it in the Workflow Builder through the Vector Database node, and in chat and custom agents through the vector_store tool.
Yes. The MultiverseAI assistant and your custom agents can call the vector_store tool, acting through the Pinecone & Qdrant account you connected. Actions that send or post can require your approval first.
Connecting Pinecone & Qdrant costs nothing extra. AI model usage in the workflows and agents that use it is billed in credits (1 credit = $0.01) or through your own provider keys. Every account starts with 100 free credits.
Create a free account, connect Pinecone & Qdrant in Connections, and build your first workflow.