AI agents call pinecone_query_vectors to retrieve information from UnClick without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
top_k | number | — | Number of nearest neighbors to return (default: 10) |
filter | object | — | Metadata filter object |
vector | array | Yes | Query vector (array of floats matching index dimension) |
api_key | string | Yes | Pinecone API key |
namespace | string | — | Namespace to query |
index_host | string | Yes | Index host URL from describe_index (e.g. https://my-index-xxx.svc.pinecone.io) |
include_values | boolean | — | Include vector values in results |
include_metadata | boolean | — | Include metadata in results (default: true) |
Parameters from the server's own tool schema.
This tool performs a vector similarity search against a Pinecone index, which is a standard read operation. It retrieves matching vectors based on similarity without creating, modifying, deleting, or executing external operations. The blast radius is minimal—misuse would return irrelevant vector results but cause no data corruption or harmful side effects.
From the tool's definition Tool name and description: 'Query a Pinecone index for nearest-neighbor vectors.' The verb 'query' combined with 'nearest-neighbor' search indicates a read-only retrieval operation with no data modification or side effects.
Risk signalsHandles credentials or secrets (api_key)
Attacks that exploit this kind of access
Query a Pinecone index for nearest-neighbor vectors. It is categorised as a Read tool in the UnClick MCP Server, which means it retrieves data without modifying state.
pinecone_query_vectors accepts 8 parameters: top_k, filter, vector, api_key, namespace, index_host, include_values, include_metadata. Required: vector, api_key, index_host. The full parameter table on this page comes from the server's own tool schema.
Register the UnClick MCP server in PolicyLayer and add a rule for pinecone_query_vectors: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches UnClick. Nothing to install.
pinecone_query_vectors is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the pinecone_query_vectors rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for pinecone_query_vectors. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
pinecone_query_vectors is provided by the UnClick MCP server (@unclick/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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