{
  "id": "resp_df551e47-12a1-408d-92da-6b0ca17a3597",
  "object": "response",
  "created_at": 1767680604,
  "status": "completed",
  "model": "/models/meta-llama/Llama-3.1-8B-Instruct",
  "output": [
    {
      "type": "mcp_list_tools",
      "id": "mcpl_8a4e6860-d111-4a1d-b7a2-1fe2b232053f",
      "server_label": "brave",
      "tools": [
        {
          "name": "brave_web_search",
          "description": "Performs a web search using the Brave Search API, ideal for general queries, news, articles, and online content. Use this for broad information gathering, recent events, or when you need diverse web sources. Supports pagination, content filtering, and freshness controls. Maximum 20 results per request, with offset for pagination. ",
          "input_schema": {
            "type": "object",
            "properties": {
              "query": {
                "type": "string",
                "description": "Search query (max 400 chars, 50 words)"
              },
              "count": {
                "type": "number",
                "description": "Number of results (1-20, default 10)",
                "default": 10
              },
              "offset": {
                "type": "number",
                "description": "Pagination offset (max 9, default 0)",
                "default": 0
              }
            },
            "required": [
              "query"
            ]
          },
          "annotations": {
            "read_only": false
          }
        },
        {
          "name": "brave_local_search",
          "description": "Searches for local businesses and places using Brave's Local Search API. Best for queries related to physical locations, businesses, restaurants, services, etc. Returns detailed information including:\n- Business names and addresses\n- Ratings and review counts\n- Phone numbers and opening hours\nUse this when the query implies 'near me' or mentions specific locations. Automatically falls back to web search if no local results are found.",
          "input_schema": {
            "type": "object",
            "properties": {
              "query": {
                "type": "string",
                "description": "Local search query (e.g. 'pizza near Central Park')"
              },
              "count": {
                "type": "number",
                "description": "Number of results (1-20, default 5)",
                "default": 5
              }
            },
            "required": [
              "query"
            ]
          },
          "annotations": {
            "read_only": false
          }
        }
      ]
    },
    {
      "type": "message",
      "id": "msg_chatcmpl-3364698a-c892-4e50-a800-4893de36311b",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "The function \"brave_web_search\" with the query \"sglang\" returns a piece of news about Sglang, a high-performance serving framework for large language models and multimodal models."
        }
      ],
      "status": "completed"
    },
    {
      "type": "mcp_call",
      "id": "mcp_799fead2-8d51-49b0-8cc6-2a91a9ca8210",
      "status": "completed",
      "arguments": "{\"query\":\"sglang\",\"count\":1,\"offset\":0}",
      "name": "brave_web_search",
      "output": "{\"content\":[{\"type\":\"text\",\"text\":\"Title: GitHub - sgl-project/sglang: SGLang is a high-performance serving framework for large language models and multimodal models.\\nDescription: SGLang is <strong>a high-performance serving framework for large language models and multimodal models</strong>. It is designed to deliver low-latency and high-throughput inference across a wide range of setups, from a single GPU to large distributed clusters.\\nURL: https://github.com/sgl-project/sglang\"}],\"isError\":false}",
      "server_label": "brave"
    }
  ],
  "parallel_tool_calls": true,
  "store": true,
  "temperature": 1,
  "tool_choice": "\"auto\"",
  "tools": [
    {
      "type": "mcp",
      "server_url": "http://localhost:8001/sse",
      "server_label": "brave",
      "server_description": "A Tool to do web search",
      "require_approval": "never"
    }
  ],
  "top_p": 1,
  "usage": {
    "prompt_tokens": 707,
    "completion_tokens": 40,
    "total_tokens": 747
  },
  "metadata": {}
}

{
  "id": "resp_66ca2fda-f4eb-49b7-8640-f03be3058a91",
  "object": "response",
  "created_at": 1767680707,
  "status": "completed",
  "model": "/models/meta-llama/Llama-3.1-8B-Instruct",
  "output": [
    {
      "type": "mcp_list_tools",
      "id": "mcpl_a00ebe03-5d3f-4f72-8211-7f695b4e7e6c",
      "server_label": "deepwiki",
      "tools": [
        {
          "name": "read_wiki_contents",
          "description": "View documentation about a GitHub repository",
          "input_schema": {
            "type": "object",
            "properties": {
              "repoName": {
                "type": "string",
                "description": "GitHub repository: owner/repo (e.g. \"facebook/react\")"
              }
            },
            "required": [
              "repoName"
            ],
            "additionalProperties": false,
            "$schema": "http://json-schema.org/draft-07/schema#"
          },
          "annotations": {
            "read_only": false
          }
        },
        {
          "name": "ask_question",
          "description": "Ask any question about a GitHub repository",
          "input_schema": {
            "type": "object",
            "properties": {
              "repoName": {
                "type": "string",
                "description": "GitHub repository: owner/repo (e.g. \"facebook/react\")"
              },
              "question": {
                "type": "string",
                "description": "The question to ask about the repository"
              }
            },
            "required": [
              "repoName",
              "question"
            ],
            "additionalProperties": false,
            "$schema": "http://json-schema.org/draft-07/schema#"
          },
          "annotations": {
            "read_only": false
          }
        },
        {
          "name": "read_wiki_structure",
          "description": "Get a list of documentation topics for a GitHub repository",
          "input_schema": {
            "type": "object",
            "properties": {
              "repoName": {
                "type": "string",
                "description": "GitHub repository: owner/repo (e.g. \"facebook/react\")"
              }
            },
            "required": [
              "repoName"
            ],
            "additionalProperties": false,
            "$schema": "http://json-schema.org/draft-07/schema#"
          },
          "annotations": {
            "read_only": false
          }
        }
      ]
    },
    {
      "type": "message",
      "id": "msg_chatcmpl-27732c9e-7f2e-45f1-8fba-832462c7563d",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "The function `ask_question` is called with the repository `facebook/sglang` and the question \"What is one simple news about sglang?\". However, since `facebook/sglang` is not a valid repository, the function returns an error message. To get the news, you need to index the repository first by visiting the provided link."
        }
      ],
      "status": "completed"
    },
    {
      "type": "mcp_call",
      "id": "mcp_66b0deee-95f4-4397-9bdd-21221c386660",
      "status": "completed",
      "arguments": "{\"question\":\"What is one simple news about sglang?\",\"repoName\":\"facebook/sglang\"}",
      "name": "ask_question",
      "output": "{\"content\":[{\"type\":\"text\",\"text\":\"Error processing question: Repository not found. Visit https://deepwiki.com/facebook/sglang to index it.\"}]}",
      "server_label": "deepwiki"
    }
  ],
  "parallel_tool_calls": true,
  "store": true,
  "temperature": 1,
  "tool_choice": "\"auto\"",
  "tools": [
    {
      "type": "mcp",
      "server_url": "https://mcp.deepwiki.com/mcp",
      "server_label": "deepwiki",
      "require_approval": "never"
    }
  ],
  "top_p": 1,
  "usage": {
    "prompt_tokens": 602,
    "completion_tokens": 72,
    "total_tokens": 674
  },
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}