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ActionPineconeUpdated June 2026

How do I run k-NN search in Pinecone?

Short answer: You can query pinecone vectors in Pinecone by hand from its own interface, but it won’t repeat itself. On TinyCommand, add the Pinecone Query Pinecone Vectors action to a workflow, map its 4 inputs from any upstream app, and it runs automatically every time the trigger fires. No code, and a free tier to start.

Query Pinecone Vectors in Pinecone — start free All 6 Pinecone actions
Query Pinecone Vectors in Pinecone — start free
Inputs

The fields this action accepts.

Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.

FieldTypeRequiredDescription
Query Vector (JSON array)
vector
stringRequiredThe embedding vector to search with
Top K
topK
stringRequiredNumber of nearest results to return
Namespace
namespace
stringOptionalNamespace. Example: default
Include Metadata
includeMetadata
optionsOptionalInclude Metadata. Options: Yes, No
Sample request
{
  "vector": "[0.1, 0.2, 0.3, ...]",
  "topK": "10",
  "namespace": "e.g. default",
  "includeMetadata": "{{trigger.includeMetadata}}"
}
Returns
{
  "matches": [
    {
      "id": "doc1",
      "score": 0.95,
      "metadata": {
        "text": "Relevant document text..."
      }
    }
  ],
  "namespace": "default"
}

Use these fields in downstream nodes for routing, logging, or error handling.

Triggered by

Apps that pair well as the trigger for Query Pinecone Vectors.

Any of these apps can fire this action as part of a workflow.

Gmail → Pinecone
1 Gmail triggers
Slack → Pinecone
13 Slack triggers
Google Sheets → Pinecone
2 Google Sheets triggers
HubSpot → Pinecone
18 HubSpot triggers
FAQ

Questions about Query Pinecone Vectors.

What does the Query Pinecone Vectors action do in Pinecone?
Returns top-k nearest vectors with scores and metadata, optionally filtered by metadata. The standard RAG retrieval call — fetch top vectors, pass metadata to LLM for grounded answers.
What inputs does Query Pinecone Vectors require?
Required: Query Vector (JSON array), Top K. Every input accepts a static value or a variable from any upstream node in your workflow.
Can I use dynamic inputs from earlier workflow nodes?
Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.
What happens if Pinecone returns an error?
The workflow pauses on the failed node, the error message is captured in the run log, and you can retry the run with one click. Auto-retry policies are configurable per workflow with exponential backoff up to 5 attempts.
Does Query Pinecone Vectors support batch operations?
Yes. Run Query Pinecone Vectors inside a Loop node to process arrays. TinyCommand handles Pinecone's rate limits automatically so you don't have to throttle manually.
More actions

Other Pinecone actions.

Action
Delete Pinecone Vectors
Removes vectors by ID list, by metadata filter, or by namespace. For "user churned → delete all their vectors" tenant-isolation workflows.
Action
Describe Pinecone Index
Returns the index's dimension, metric, host, status. Useful for "is the index ready?" pre-flight checks before query workflows.
Action
Describe Pinecone Index Stats
Returns vector count by namespace. Useful for capacity planning and for "did the bulk insert succeed?" post-operation verification.
Action
List Pinecone Indexes
Returns every index in the connected project. Useful for inventory and for resolving index names at workflow setup.
Action
Upsert Pinecone Vectors
Batch-inserts up to 100 vectors with metadata and namespace. For bulk ingestion >100, pre-batch upstream. The standard "embed content → index in Pinecone" step.
Query Pinecone Vectors in Pinecone — start free