MCP Tool · x402 · early usage

Ask a question, get a short cited answer in one call

Name: Ask a question, get a short cited answer in one call
Price: 0.01 USD
Availability: InStock

by x402-seller-pmlm.onrender.com · discovered, not yet claimed by its owner · updated 2026-10-10

30d calls9

30d payers4

MethodGET

Outputjson

Mirrored from Coinbase's public x402 Bazaar. The description is the provider's own text and has not been reviewed here; the payment requirements are copied as published.

What it does

Ask a question, get a short cited answer in one call. Returns a 1-3 sentence answer, key points tied to source ids, and the sources used (typically 1-5: title, URL, publisher, date, supporting quote), plus confidence with a reason and a free permalink. Sources: Wikipedia first, plus Stack Overflow, GitHub, Crossref papers, official docs when relevant. Best for definitions, overviews, how-it-works, history. Example: "What is the Model Context Protocol?". 0.01 USDC/call; failed calls are free.

Tags: research brief · web research · summarize a topic · wikipedia summary · answer a question with sources · bazaar · builder-code · eip2612GasSponsoring · erc20ApprovalGasSponsoring

Call contract

Method: GET
Input: query parameters
Output: json
Last paid call: 2026-10-10

Input example from Bazaar metadata

{
  "q": "What is the Model Context Protocol?"
}

Output example

{
  "answer": "The Model Context Protocol (MCP) is an open standard and open-source framework introduced by Anthropic in November 2024 to standardize the way artificial intelligence (AI) systems like large language models (LLMs) integrate and share data with external tools, systems, and data sources. MCP provides a standardized interface for reading files, executing functions, and handling contextual prompts.",
  "answer_citations": [
    1
  ],
  "checked_at": "2026-10-09T17:43:22.098Z",
  "confidence": "high",
  "confidence_why": "3 cited sources from 2 publisher(s), no primary/authoritative source found.",
  "key_points": [
    {
      "citations": [
        2
      ],
      "text": "This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources."
    },
    {
      "citations": [
        3
      ],
      "text": "The Model Context Protocol lets you build servers that expose data and functionality to LLM applications in a secure, standardized way."
    }
  ],
  "latencyMs": 1087,
  "method": "extractive (Wikipedia lead + ranked sentences)",
  "permalink": "https://x402-seller-pmlm.onrender.com/a/example-mcp",
  "query": "What is the Model Context Protocol?",
  "sourceCount": 3,
  "sources": [
    {
      "id": 1,
      "published": "2026-10-06",
      "publisher": "Wikipedia",
      "quote": "The Model Context Protocol (MCP) is an open standard and open-source framework introduced by Anthropic in November 2024 to standardize the way artificial intelligence (AI) systems like large language models (LLMs)…",
      "title": "Model Context Protocol",
      "type": "encyclopedia",
      "url": "https://en.wikipedia.org/wiki/Model_Context_Protocol"
    },
    {
      "id": 2,
      "published": "2026-10-07",
      "publisher": "GitHub",
      "quote": "This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources.",
      "title": "modelcontextprotocol/servers: Model Context Protocol Servers",
      "type": "web_page",
      "url": "https://github.com/modelcontextprotocol/servers"
    },
    {
      "id": 3,
      "published": "2026-10-05",
      "publisher": "GitHub",
      "quote": "The Model Context Protocol lets you build servers that expose data and functionality to LLM applications in a secure, standardized way.",
      "title": "modelcontextprotocol/python-sdk: The official Python SDK for Model Context Protocol servers and clients",
      "type": "web_page",
      "url": "https://github.com/modelcontextprotocol/python-sdk"
    }
  ]
}

Use with an agent

Discover. Agents find this listing with GET https://bazaar.saylorinnovations.com/discovery/search?query=…, the MCP tool search_resources, or /discovery/resources.
Inspect. Fetch /resources/28407.json for the price and payment options.
Pay. Call GET https://x402-seller-pmlm.onrender.com/report. The provider answers 402 with its payment requirements. An x402 client signs one of the options below and retries with PAYMENT-SIGNATURE.
Execute. The provider returns 200 with the data. Agent Bazaar is not in the request path and never sees your payment.

For humans

You don't need an account or an API key; you need a wallet holding a small amount of USDC on Base, Polygon, Arbitrum One, Solana, Avalanche, eip155:1329, and an x402-capable client (see the examples below). Call the endpoint unpaid first to see exactly what it asks for.

Pricing & payment

Price: $0.01 / request
Protocol: x402 v2
Auth: No account or API key. Pay per request.
Networks: Base, Polygon, Arbitrum One, Solana, Avalanche, eip155:1329
Demand: 9 calls · 4 unique payers in 30d (public x402 Bazaar data)

x402 payment requirements

Scheme	Network	Asset	Amount	Pay to	Timeout
exact	Base eip155:8453	USDC	$0.01	0x079471E6F43b6feeF80895E19cBFcBB496904852	300s
exact	Polygon eip155:137	USDC	$0.01	0x079471E6F43b6feeF80895E19cBFcBB496904852	300s
exact	Arbitrum One eip155:42161	USDC	$0.01	0x079471E6F43b6feeF80895E19cBFcBB496904852	300s
exact	Solana solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp	USDC	$0.01	787RZwDGpjmRsG5wgnyBeWQHBuARax8Qo6P7dmDuqKeW	300s
exact	Avalanche eip155:43114	0xB97EF9Ef8734C71904D8002F8b6Bc66Dd9c48a6E	10000	0x079471E6F43b6feeF80895E19cBFcBB496904852	300s
exact	eip155:1329 eip155:1329	0xe15fC38F6D8c56aF07bbCBe3BAf5708A2Bf42392	10000	0x079471E6F43b6feeF80895E19cBFcBB496904852	300s

accepts[] (raw JSON)

[
  {
    "scheme": "exact",
    "network": "eip155:8453",
    "payTo": "0x079471E6F43b6feeF80895E19cBFcBB496904852",
    "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
    "amount": "10000",
    "amountUsd": 0.01,
    "maxTimeoutSeconds": 300
  },
  {
    "scheme": "exact",
    "network": "eip155:137",
    "payTo": "0x079471E6F43b6feeF80895E19cBFcBB496904852",
    "asset": "0x3c499c542cEF5E3811e1192ce70d8cC03d5c3359",
    "amount": "10000",
    "amountUsd": 0.01,
    "maxTimeoutSeconds": 300
  },
  {
    "scheme": "exact",
    "network": "eip155:42161",
    "payTo": "0x079471E6F43b6feeF80895E19cBFcBB496904852",
    "asset": "0xaf88d065e77c8cC2239327C5EDb3A432268e5831",
    "amount": "10000",
    "amountUsd": 0.01,
    "maxTimeoutSeconds": 300
  },
  {
    "scheme": "exact",
    "network": "solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp",
    "payTo": "787RZwDGpjmRsG5wgnyBeWQHBuARax8Qo6P7dmDuqKeW",
    "asset": "EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v",
    "amount": "10000",
    "amountUsd": 0.01,
    "maxTimeoutSeconds": 300
  },
  {
    "scheme": "exact",
    "network": "eip155:43114",
    "payTo": "0x079471E6F43b6feeF80895E19cBFcBB496904852",
    "asset": "0xB97EF9Ef8734C71904D8002F8b6Bc66Dd9c48a6E",
    "amount": "10000",
    "maxTimeoutSeconds": 300
  },
  {
    "scheme": "exact",
    "network": "eip155:1329",
    "payTo": "0x079471E6F43b6feeF80895E19cBFcBB496904852",
    "asset": "0xe15fC38F6D8c56aF07bbCBe3BAf5708A2Bf42392",
    "amount": "10000",
    "maxTimeoutSeconds": 300
  }
]

Schemas

Output schema (JSON Schema)

{
  "properties": {
    "example": {
      "properties": {
        "answer": {
          "description": "1-3 sentence direct answer (plain text; ids in answer_citations)",
          "type": "string"
        },
        "answer_citations": {
          "description": "source ids supporting the answer",
          "items": {
            "type": "integer"
          },
          "type": "array"
        },
        "bullets": {
          "description": "Key points, each with [n] citations",
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        "cached": {
          "type": "boolean"
        },
        "checked_at": {
          "description": "ISO time the sources were checked",
          "type": "string"
        },
        "confidence": {
          "description": "high = 3+ cited sources from 2+ providers or 2+ primary/authoritative publishers",
          "enum": [
            "high",
            "medium",
            "low"
          ],
          "type": "string"
        },
        "confidenceBasis": {
          "type": "string"
        },
        "confidence_why": {
          "description": "One line: why this confidence level",
          "type": "string"
        },
        "depth": {
          "type": "string"
        },
        "generatedAt": {
          "type": "string"
        },
        "key_points": {
          "description": "Key points, each tied to the source ids that support it",
          "items": {
            "properties": {
              "citations": {
                "items": {
                  "type": "integer"
                },
                "type": "array"
              },
              "text": {
                "type": "string"
              }
            },
            "required": [
              "text",
              "citations"
            ],
            "type": "object"
          },
          "type": "array"
        },
        "lang": {
          "type": "string"
        },
        "latencyMs": {
          "type": "integer"
        },
        "method": {
          "description": "extractive, extractive (Wikipedia lead + ranked sentences), or llm-synthesis:<model>",
          "type": "string"
        },
        "next": {
          "description": "Suggested follow-up calls",
          "items": {
            "properties": {
              "call": {
                "type": "string"
              },
              "endpoint": {
                "type": "string"
              },
              "why": {
                "type": "string"
              }
            },
            "type": "object"
          },
          "type": "array"
        },
        "permalink": {
          "description": "Free shareable page for this answer (/a/<id>; add ?format=json). Kept in memory, may reset on redeploy",
          "type": "string"
        },
        "providers": {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        "query": {
          "type": "string"
        },
        "sourceCount": {
          "type": "integer"
        },
        "sources": {
          "items": {
            "properties": {
              "id": {
                "type": "integer"
              },
              "provider": {
                "type": "string"
              },
              "published": {
                "description": "YYYY-MM-DD when known",
                "type": [
                  "string",
                  "null"
                ]
              },
              "publishedAt": {
                "type": [
                  "string",
                  "null"
                ]
              },
              "publisher": {
                "type": "string"
              },
              "quote": {
                "description": "Sentence from this source that supports the cited claim",
                "type": "string"
              },
              "snippet": {
                "type": "string"
              },
              "title": {
                "type": "string"
              },
              "type": {
                "enum": [
                  "encyclopedia",
                  "instant_answer",
                  "discussion",
                  "paper",
                  "web_page"
                ],
                "type": "string"
              },
              "url": {
                "type": "string"
              }
            },
            "required": [
              "id",
              "title",
              "url"
            ],
            "type": "object"
          },
          "type": "array"
        },
        "summary": {
          "description": "Same answer with inline [n] citations",
          "type": "string"
        },
        "topic": {
          "description": "Topic extracted from q (request words like 'summarize' removed)",
          "type": "string"
        },
        "wikipedia": {
          "description": "Wikipedia summary card for the topic, when one matches",
          "properties": {
            "description": {
              "type": [
                "string",
                "null"
              ]
            },
            "extract": {
              "type": "string"
            },
            "lastEdited": {
              "type": [
                "string",
                "null"
              ]
            },
            "thumbnail": {
              "type": [
                "string",
                "null"
              ]
            },
            "title": {
              "type": "string"
            },
            "url": {
              "type": "string"
            },
            "wikidataId": {
              "type": [
                "string",
                "null"
              ]
            }
          },
          "type": [
            "object",
            "null"
          ]
        }
      },
      "required": [
        "answer",
        "key_points",
        "sources",
        "confidence",
        "checked_at",
        "query"
      ],
      "type": "object"
    },
    "type": {
      "type": "string"
    }
  },
  "required": [
    "type"
  ],
  "type": "object"
}

Example shape — generated from the schema, not a captured live response

{
  "example": {
    "answer": "string",
    "answer_citations": [
      0
    ],
    "bullets": [
      "string"
    ],
    "cached": true,
    "checked_at": "string",
    "confidence": "high",
    "confidenceBasis": "string",
    "confidence_why": "string",
    "depth": "string",
    "generatedAt": "string",
    "key_points": [
      {
        "citations": [
          0
        ],
        "text": "string"
      }
    ],
    "lang": "string",
    "latencyMs": 0,
    "method": "string",
    "next": [
      {
        "call": "string",
        "endpoint": "string",
        "why": "string"
      }
    ],
    "permalink": "string",
    "providers": [
      "string"
    ],
    "query": "string",
    "sourceCount": 0,
    "sources": [
      {
        "id": 0,
        "provider": "string",
        "published": "string",
        "publishedAt": "string",
        "publisher": "string",
        "quote": "string",
        "snippet": "string",
        "title": "string",
        "type": "encyclopedia",
        "url": "string"
      }
    ],
    "summary": "string",
    "topic": "string",
    "wikipedia": {
      "description": "string",
      "extract": "string",
      "lastEdited": "string",
      "thumbnail": "string",
      "title": "string",
      "url": "string",
      "wikidataId": "string"
    }
  },
  "type": "string"
}

Examples

curl

curl "https://x402-seller-pmlm.onrender.com/report"
# -> 402 Payment Required, accepts[] lists how to pay
# retry with a PAYMENT-SIGNATURE (or PAYMENT header) once paid

JavaScript

const res = await fetch("https://x402-seller-pmlm.onrender.com/report");
if (res.status === 402) {
  const { accepts } = await res.json();
  // pay one of accepts[] via an x402 client, then retry with the payment header
}

Python

import httpx
res = httpx.get("https://x402-seller-pmlm.onrender.com/report")
if res.status_code == 402:
    accepts = res.json()["accepts"]
    # pay one of accepts[] via an x402 client, then retry with the payment header

Details

Provider: x402-seller-pmlm.onrender.com
Endpoint: https://x402-seller-pmlm.onrender.com/report
Machine-readable: /resources/28407.json