AI agent? Read this page as Markdown at /genai/prompt/Create_a_prompt.md — append .md to any docs URL, or start from /llms.txt.

Create a prompt

POST/genai/{connection_id}/prompt

Parameters

fieldsstring array
Fields to return
rawstring
Raw parameters to include in the 3rd-party request. Encoded as a URL component. eg. raw parameters: foo=bar&zoo=bar -> raw=foo%3Dbar%26zoo%3Dbar
connection_idstring required
ID of the connection

Payload

model_idstring
messages array
temperaturenumber
0-1
max_tokensnumber
a float between 0-1
responsesstring array
tokens_usednumber
mcp_urlstring
Supply a remote MCP URL to send to the LLM API for it to call its tools. Note: Some LLM APIs do not yet support remote MCP URLs.
mcp_deferred_toolsstring array
mcp_authorization_tokenstring
OAuth Bearer token for MCP servers that require authentication.
questions array
Typed questions to evaluate against the messages (for decision models such as TypeSafe Jev).
answers array
One answer per question, matched by id.

Returns

model_idstring
messages array
temperaturenumber
0-1
max_tokensnumber
a float between 0-1
responsesstring array
tokens_usednumber
mcp_urlstring
Supply a remote MCP URL to send to the LLM API for it to call its tools. Note: Some LLM APIs do not yet support remote MCP URLs.
mcp_deferred_toolsstring array
mcp_authorization_tokenstring
OAuth Bearer token for MCP servers that require authentication.
questions array
Typed questions to evaluate against the messages (for decision models such as TypeSafe Jev).
answers array
One answer per question, matched by id.
const options = {
  method: 'POST',
  url: 'https://api.unified.to/genai/5de520f96e439b002043d8dc/prompt',
  headers: {
    authorization: 'bearer .....'
  },
  data: undefined,
  params: {
    fields: '',
    raw: '',
  }
};

const results = await axios.request(options);
Are we missing anything? Let us know
Was this page helpful?