openai_create_embedding
Create vector embeddings for text using an OpenAI embedding model.
This record as markdown: /tools/io-github-malamutemayhem-unclick-mcp-server/openai-create-embedding.md
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.
| Parameter | Type | Required | Description |
|---|---|---|---|
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 is rated High
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)
Attacks that exploit this kind of access
The rule that runs openai_create_embedding safely
PolicyLayer is an MCP gateway: it sits between your AI agents and UnClick, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For openai_create_embedding, this is the rule to start with:
openai_create_embedding stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect UnClick, apply this rule, and every openai_create_embedding call is checked against it from then on.
Questions about openai_create_embedding
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.
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.
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.
openai_create_embedding is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
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.
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.
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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