openai_create_embedding

Create vector embeddings for text using an OpenAI embedding model.

Server UnClick @unclick/mcp-server
Category Execute
Risk class High
Parameters 52 required

What openai_create_embedding does on UnClick

AI agents invoke openai_create_embedding to trigger actions in UnClick. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

ParameterTypeRequiredDescription
input object Yes String or array of strings to embed
model string Embedding model (default: text-embedding-3-small)
org_id string
api_key string Yes
dimensions number Number of output dimensions (for text-embedding-3-* models)

Parameters from the server's own tool schema.

Why openai_create_embedding needs a policy

This tool triggers an external API call to OpenAI's embedding service, which constitutes executing an external operation. It sends data to a third-party service (OpenAI), incurring API usage/costs and transmitting potentially sensitive text externally. It is not a simple local read, and its effects (API calls, cost, data transmission) depend on the input arguments.

From the tool's definition "Create vector embeddings for text using an OpenAI embedding model"

Risk signalsHandles credentials or secrets (api_key)

Questions about openai_create_embedding

What does the openai_create_embedding tool do? +

Create vector embeddings for text using an OpenAI embedding model. It is categorised as a Execute tool in the UnClick MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does openai_create_embedding accept? +

openai_create_embedding accepts 5 parameters: input, model, org_id, api_key, dimensions. Required: input, api_key. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on openai_create_embedding? +

Register the UnClick MCP server in PolicyLayer and add a rule for openai_create_embedding: 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.

What risk level is openai_create_embedding? +

openai_create_embedding is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit openai_create_embedding? +

Yes. Add a rate_limit block to the openai_create_embedding 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.

How do I block openai_create_embedding completely? +

Set action: deny in the PolicyLayer policy for openai_create_embedding. 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.

What MCP server provides openai_create_embedding? +

openai_create_embedding 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.

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