Search your files in a response

from openai import OpenAI
client = OpenAI()

response = client.responses.create(
    model="gpt-4.1",
    input="What is deep research by OpenAI?",
    tools=[{
        "type": "file_search",
        "vector_store_ids": ["<vector_store_id>"]
    }]
)
print(response)

import OpenAI from "openai";
const openai = new OpenAI();

const response = await openai.responses.create({
    model: "gpt-4.1",
    input: "What is deep research by OpenAI?",
    tools: [
        {
            type: "file_search",
            vector_store_ids: ["<vector_store_id>"],
        },
    ],
});
console.log(response);

using OpenAI.Responses;

string key = Environment.GetEnvironmentVariable("OPENAI_API_KEY")!;
OpenAIResponseClient client = new(model: "gpt-5", apiKey: key);

ResponseCreationOptions options = new();
options.Tools.Add(ResponseTool.CreateFileSearchTool(["<vector_store_id>"]));

OpenAIResponse response = (OpenAIResponse)client.CreateResponse([
    ResponseItem.CreateUserMessageItem([
        ResponseContentPart.CreateInputTextPart("What is deep research by OpenAI?"),
    ]),
], options);

Console.WriteLine(response.GetOutputText());

Call a remote MCP server

curl https://api.openai.com/v1/responses \\ 
-H "Content-Type: application/json" \\ 
-H "Authorization: Bearer $OPENAI_API_KEY" \\ 
-d '{
  "model": "gpt-5",
    "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/sse",
        "require_approval": "never"
      }
    ],
    "input": "Roll 2d4+1"
  }'

import OpenAI from "openai";
const client = new OpenAI();

const resp = await client.responses.create({
  model: "gpt-5",
  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/sse",
      require_approval: "never",
    },
  ],
  input: "Roll 2d4+1",
});

console.log(resp.output_text);

from openai import OpenAI

client = OpenAI()

resp = client.responses.create(
    model="gpt-5",
    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/sse",
            "require_approval": "never",
        },
    ],
    input="Roll 2d4+1",
)

print(resp.output_text)

using OpenAI.Responses;

string key = Environment.GetEnvironmentVariable("OPENAI_API_KEY")!;
OpenAIResponseClient client = new(model: "gpt-5", apiKey: key);

ResponseCreationOptions options = new();
options.Tools.Add(ResponseTool.CreateMcpTool(
    serverLabel: "dmcp",
    serverUri: new Uri("https://dmcp-server.deno.dev/sse"),
    toolCallApprovalPolicy: new McpToolCallApprovalPolicy(GlobalMcpToolCallApprovalPolicy.NeverRequireApproval)
));

OpenAIResponse response = (OpenAIResponse)client.CreateResponse([
    ResponseItem.CreateUserMessageItem([
        ResponseContentPart.CreateInputTextPart("Roll 2d4+1")
    ])
], options);

Console.WriteLine(response.GetOutputText());