as per documentation https://developers.openai.com/api/docs/guides/tools-connectors-mcp
the first example is:
from openai import OpenAI
client = OpenAI()
resp = client.responses.create(
model="gpt-5.6",
tools=[
{
"type": "mcp",
"server_label": "dmcp",
"server_description": "A Dungeons and Dragons MCP server to assist with dice rolling.",
"server_url": "https://dmcp-server.deno.dev/mcp",
"require_approval": "never",
},
],
input="Roll 2d4+1",
)
which is the current supported shape in our gateway so far. since our current agentic loop not handling the approval path we can support that later.
The shape of require_approval : { "never": {"tool_names":[]}} is specific to filtering approval.
with example:
from openai import OpenAI
client = OpenAI()
resp = client.responses.create(
model="gpt-5.6",
tools=[
{
"type": "mcp",
"server_label": "deepwiki",
"server_url": "https://mcp.deepwiki.com/mcp",
"require_approval": {
"never": {
"tool_names": ["ask_question", "read_wiki_structure"]
}
}
},
],
input="What transport protocols does the 2025-03-26 version of the MCP spec (modelcontextprotocol/modelcontextprotocol) support?",
)
will make this comment to an issue for this to add for future support.
Originally posted by @maralbahari in #138 (comment)
as per documentation https://developers.openai.com/api/docs/guides/tools-connectors-mcp
the first example is:
which is the current supported shape in our gateway so far. since our current agentic loop not handling the approval path we can support that later.
The shape of
require_approval : { "never": {"tool_names":[]}}is specific to filtering approval.with example:
will make this comment to an issue for this to add for future support.
Originally posted by @maralbahari in #138 (comment)