openai.AsyncResponsesTool

An async Responses function tool that preserves Console text and images.

Usage

openai.AsyncResponsesTool(console, tool)

Create this through responses_tool() with an AsyncMCPConsole. Use definition when requesting a model response, then await tool(call) to build the next request’s function-call output. The factory page shows the complete model loop.

Examples

Install with pip install 'mcp-console[openai]'. You can also invoke call() directly to inspect the output without a model or API key:

import asyncio
import mcp_console
from mcp_console import AsyncMCPConsole


async def main():
    async with AsyncMCPConsole() as console:
        tool = mcp_console.openai.responses_tool(console)
        output = await tool.call(
            {"python": "sum([12, 15, 18, 20, 25])"}
        )
        print(output)


asyncio.run(main())

Attributes

Name	Description
definition	Function-tool definition to place in `responses.create(tools=...)`.

definition

Function-tool definition to place in responses.create(tools=...).

definition: dict[str, Any]

Methods

Name	Description
call()	Execute `send` arguments supplied as a JSON string or mapping.
output()	Execute a model function call and return its `function_call_output`.

call()

Execute send arguments supplied as a JSON string or mapping.

Usage

Source

call(arguments)

Returns text for text-only output, or Responses input_text and input_image blocks for rich output. A model call’s arguments can be passed directly; output() also attaches its call_id.

output()

Execute a model function call and return its function_call_output.

Usage

Source

output(call)

Accepts a Responses function-call object or a mapping with call_id and arguments. Pass the returned item in the next request’s input. await tool(call) is shorthand for await tool.output(call).