MCP 与连接器

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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",
        "allowed_tools": ["roll"]
      }
    ],
    "input": "Roll 2d4+1"
  }'

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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",
    allowed_tools: ["roll"],
  }],
  input: "Roll 2d4+1",
});

console.log(resp.output_text);

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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"),
    allowedTools: new McpToolFilter() { ToolNames = { "roll" } },
    toolCallApprovalPolicy: new McpToolCallApprovalPolicy(GlobalMcpToolCallApprovalPolicy.NeverRequireApproval)
));

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

Console.WriteLine(response.GetOutputText());

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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": "always",
      }
    ],
    "previous_response_id": "resp_682d498bdefc81918b4a6aa477bfafd904ad1e533afccbfa",
    "input": [{
      "type": "mcp_approval_response",
      "approve": true,
      "approval_request_id": "mcpr_682d498e3bd4819196a0ce1664f8e77b04ad1e533afccbfa"
    }]
  }'

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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: "always",
  }],
  previous_response_id: "resp_682d498bdefc81918b4a6aa477bfafd904ad1e533afccbfa",
  input: [{
    type: "mcp_approval_response",
    approve: true,
    approval_request_id: "mcpr_682d498e3bd4819196a0ce1664f8e77b04ad1e533afccbfa"
  }],
});

console.log(resp.output_text);

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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.AlwaysRequireApproval)
));

// STEP 1: Create response that requests tool call approval
OpenAIResponse response1 = (OpenAIResponse)client.CreateResponse([
    ResponseItem.CreateUserMessageItem([
        ResponseContentPart.CreateInputTextPart("Roll 2d4+1")
    ])
], options);

McpToolCallApprovalRequestItem? approvalRequestItem = response1.OutputItems.Last() as McpToolCallApprovalRequestItem;

// STEP 2: Approve the tool call request and get final response
options.PreviousResponseId = response1.Id;
OpenAIResponse response2 = (OpenAIResponse)client.CreateResponse([
    ResponseItem.CreateMcpApprovalResponseItem(approvalRequestItem!.Id, approved: true),
], options);

Console.WriteLine(response2.GetOutputText());

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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": "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?"
  }'

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

const resp = await client.responses.create({
  model: "gpt-5",
  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?",
});

console.log(resp.output_text);

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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: "deepwiki",
    serverUri: new Uri("https://mcp.deepwiki.com/mcp"),
    allowedTools: new McpToolFilter() { ToolNames = { "ask_question", "read_wiki_structure" } },
    toolCallApprovalPolicy: new McpToolCallApprovalPolicy(GlobalMcpToolCallApprovalPolicy.NeverRequireApproval)
));

OpenAIResponse response = (OpenAIResponse)client.CreateResponse([
    ResponseItem.CreateUserMessageItem([
        ResponseContentPart.CreateInputTextPart("What transport protocols does the 2025-03-26 version of the MCP spec (modelcontextprotocol/modelcontextprotocol) support?")
    ])
], options);

Console.WriteLine(response.GetOutputText());

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curl https://api.openai.com/v1/responses \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENAI_API_KEY" \
-d '{
    "model": "gpt-5",
    "input": "Create a payment link for $20",
    "tools": [
      {
        "type": "mcp",
        "server_label": "stripe",
        "server_url": "https://mcp.stripe.com",
        "authorization": "$STRIPE_OAUTH_ACCESS_TOKEN"
      }
    ]
  }'

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

const resp = await client.responses.create({
  model: "gpt-5",
  input: "Create a payment link for $20",
  tools: [
    {
      type: "mcp",
      server_label: "stripe",
      server_url: "https://mcp.stripe.com",
      authorization: "$STRIPE_OAUTH_ACCESS_TOKEN"
    }
  ]
});

console.log(resp.output_text);

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using OpenAI.Responses;

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

ResponseCreationOptions options = new();
options.Tools.Add(ResponseTool.CreateMcpTool(
    serverLabel: "stripe",
    serverUri: new Uri("https://mcp.stripe.com"),
    authorizationToken: authToken
));

OpenAIResponse response = (OpenAIResponse)client.CreateResponse([
    ResponseItem.CreateUserMessageItem([
        ResponseContentPart.CreateInputTextPart("Create a payment link for $20")
    ])
], options);

Console.WriteLine(response.GetOutputText());

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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": "google_calendar",
        "connector_id": "connector_googlecalendar",
        "authorization": "ya29.A0AS3H6...",
        "require_approval": "never"
      }
    ],
    "input": "What is on my Google Calendar for today?"
  }'

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

const resp = await client.responses.create({
  model: "gpt-5",
  tools: [
    {
      type: "mcp",
      server_label: "google_calendar",
      connector_id: "connector_googlecalendar",
      authorization: "ya29.A0AS3H6...",
      require_approval: "never",
    },
  ],
  input: "What's on my Google Calendar for today?",
});

console.log(resp.output_text);

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using OpenAI.Responses;

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

ResponseCreationOptions options = new();
options.Tools.Add(ResponseTool.CreateMcpTool(
    serverLabel: "google_calendar",
    connectorId: McpToolConnectorId.GoogleCalendar,
    authorizationToken: authToken,
    toolCallApprovalPolicy: new McpToolCallApprovalPolicy(GlobalMcpToolCallApprovalPolicy.NeverRequireApproval)
));

OpenAIResponse response = (OpenAIResponse)client.CreateResponse([
    ResponseItem.CreateUserMessageItem([
        ResponseContentPart.CreateInputTextPart("What's on my Google Calendar for today?")
    ])
], options);

Console.WriteLine(response.GetOutputText());