magent

Deterministic published-formula arithmetic plus ICD-10-CM, RxNorm, and LOINC. Pay in USDC on Base via x402.

Searchofflineeip155:8453Exactvia cdp
Improve-vteVteThrombosisHospitalScore
Calls · 30d
2→ 0%
This endpoint's own trailing-30-day call count, as published by the upstream catalog and snapshotted daily. 13 snapshots so far.
$13.75
Verified settled volume
2,750 settlements proven x402 by their on-chain EIP-3009 marker.
$0.0050
Listed price
As published in the catalog. Always read the live 402 before paying.
2
Calls · 30d
Upstream's own call count for this endpoint, not ours.
1
Unique payers · 30d
Last called 2026-08-31 13:19Z
Upstream on-chain volume
Reported by the source catalog.
Paid to
0x836Be278f1739fB4308091cD1852F7971Bc19Ee2

The wallet the 402 directs payment to. Its whole payment record — every payer, every chain — is on the merchant page.

Asset 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913

Provider

The payTo wallet does not resolve to a registered ERC-8004 agent. That is not a verdict on the service — most of the catalog is unregistered.

Live 402 challenge

Captured by the enrichment pass, not read just now. Prices can change — always read the 402 the endpoint answers with.

{
  "error": "PAYMENT-SIGNATURE header is required",
  "accepts": [
    {
      "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
      "extra": {
        "name": "USD Coin",
        "version": "2",
        "paymentFlow": "upfront",
        "resourceUrl": "https://api.magentlab.com/api/calc/improve_vte",
        "assetTransferMethod": "eip3009"
      },
      "payTo": "0x836Be278f1739fB4308091cD1852F7971Bc19Ee2",
      "amount": "5000",
      "scheme": "exact",
      "network": "eip155:8453",
      "maxTimeoutSeconds": 600
    },
    {
      "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
      "extra": {
        "name": "USD Coin",
        "version": "2",
        "withdrawDelay": 86400,
        "receiverAuthorizer": "0x3721824a31197dcDD2984cF43b92B6cc8A87c0Fb",
        "assetTransferMethod": "eip3009"
      },
      "payTo": "0x836Be278f1739fB4308091cD1852F7971Bc19Ee2",
      "amount": "5000",
      "scheme": "batch-settlement",
      "network": "eip155:8453",
      "maxTimeoutSeconds": 600
    }
  ],
  "resource": {
    "url": "https://api.magentlab.com/api/calc/improve_vte",
    "tags": [
      "improve-vte",
      "vte",
      "thrombosis",
      "hospital",
      "score"
    ],
    "mimeType": "application/json",
    "description": "Spyropoulos 2011 7-factor associative IMPROVE VTE score during hospitalization: previous VTE 3, known thrombophilia 2, lower-limb paralysis 2, current cancer 2, immobilized >=7 days 1, ICU/CCU stay 1, age >60 1. Max 12. Bands: 0-1; 2-3 (observed VTE 1.5%); >=4 (observed VTE 5.7%). Not a VTE diagnosis or prophylaxis order. Not the 4-factor admission predictive model. Not IMPROVEDD. magent does not examine the patient.",
    "serviceName": "magent"
  },
  "extensions": {
    "bazaar": {
      "info": {
        "input": {
          "type": "http",
          "method": "GET",
          "queryParams": {
            "age": 50,
            "icu_ccu_stay": false,
            "previous_vte": false,
            "current_cancer": false,
            "known_thrombophilia": false,
            "lower_limb_paralysis": false,
            "immobilized_ge_7_days": false
          }
        },
        "output": {
          "type": "json",
          "example": {
            "score": 0,
            "formula": "improve_vte",
            "citation": {
              "id": "spyropoulos-2011",
              "doi": "10.1378/chest.10-1944",
              "pmid": "21436241",
              "title": "Predictive and associative models to identify hospitalized medical patients at risk for VTE",
              "source": "Chest. 2011;140(3):706-714",
              "authors": "Spyropoulos AC, Anderson FA Jr, FitzGerald G, Decousus H, Pini M, Chong BH, Zotz RB, Bergmann JF, Tapson VF, Froehlich JB, Monreal M, Merli GJ, Pavanello R, Turpie AGG, Nakamura M, Piovella F, Kakkar AK, Spencer FA, IMPROVE Investigators"
            },
            "vte_band": "0-1",
            "age_years": 50,
            "max_score": 12,
            "components": [
              {
                "factor": "previous_vte",
                "points": 0,
                "present": false
              },
              {
                "factor": "known_thrombophilia",
                "points": 0,
                "present": false
              },
              {
                "factor": "lower_limb_paralysis",
                "points": 0,
                "present": false
              },
              {
                "factor": "current_cancer",
                "points": 0,
                "present": false
              },
              {
                "factor": "immobilized_ge_7_days",
                "points": 0,
                "present": false
              },
              {
                "factor": "icu_ccu_stay",
                "points": 0,
                "present": false
              },
              {
                "value": 50,
                "factor": "age_gt_60",
                "points": 0,
                "present": false
              }
            ],
            "disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
            "formula_expression": "IMPROVE VTE (Spyropoulos 2011 7-factor associative during hospitalization) = previous_vte (3) + known_thrombophilia (2) + lower_limb_paralysis (2) + current_cancer (2) + immobilized_ge_7_days (1) + icu_ccu_stay (1) + age>60 (1); max 12; 0-1, 2-3 (observed VTE 1.5%), >=4 (observed VTE 5.7%); not the 4-factor admission predictive model; not IMPROVEDD"
          }
        },
        "iconUrl": "https://api.magentlab.com/favicon.ico"
      },
      "schema": {
        "type": "object",
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "required": [
          "input"
        ],
        "properties": {
          "input": {
            "type": "object",
            "required": [
              "type",
              "method"
            ],
            "properties": {
              "type": {
                "type": "string",
                "const": "http"
              },
              "method": {
                "enum": [
                  "GET",
                  "HEAD",
                  "DELETE"
                ],
                "type": "string"
              },
              "headers": {
                "type": "object",
                "additionalProperties": {
                  "type": "string"
                }
              },
              "queryParams": {
                "type": "object",
                "required": [
                  "age",
                  "previous_vte",
                  "known_thrombophilia",
                  "lower_limb_paralysis",
                  "current_cancer",
                  "immobilized_ge_7_days",
                  "icu_ccu_stay"
                ],
                "properties": {
                  "age": {
                    "type": "integer",
                    "description": "Age in years (18-120). Scores 1 when age >60 (Spyropoulos 2011). Age 60 scores 0; age 61 scores 1."
                  },
                  "icu_ccu_stay": {
                    "type": "boolean",
                    "description": "ICU or CCU stay as assigned by the caller (Spyropoulos 2011, during hospitalization). true or false. 1 point if true. magent does not assign level of care."
                  },
                  "previous_vte": {
                    "type": "boolean",
                    "description": "Previous VTE as assigned by the caller (Spyropoulos 2011 7-factor associative model). true or false. 3 points if true. magent does not diagnose VTE."
                  },
                  "current_cancer": {
                    "type": "boolean",
                    "description": "Current cancer as assigned by the caller (Spyropoulos 2011). true or false. 2 points if true. magent does not diagnose cancer."
                  },
                  "known_thrombophilia": {
                    "type": "boolean",
                    "description": "Known thrombophilia as assigned by the caller (Spyropoulos 2011). true or false. 2 points if true. magent does not interpret a thrombophilia panel."
                  },
                  "lower_limb_paralysis": {
                    "type": "boolean",
                    "description": "Lower-limb paralysis as assigned by the caller (Spyropoulos 2011). true or false. 2 points if true. magent does not examine the patient."
                  },
                  "immobilized_ge_7_days": {
                    "type": "boolean",
                    "description": "Immobilized ≥7 days as assigned by the caller (Spyropoulos 2011, during hospitalization). true or false. 1 point if true. magent does not observe mobility."
                  }
                }
              }
            },
            "additionalProperties": false
          },
          "output": {
            "type": "object",
            "required": [
              "type"
            ],
            "properties": {
              "type": {
                "type": "string"
              },
              "example": {
                "type": "object"
              }
            }
          }
        }
      }
    }
  },
  "x402Version": 2
}

Accepts

The payment requirements as published to the catalog. Read the live 402 before paying — a price here is a claim, not a quote.

0.005USDC≈ $0.005 USD
on Base · exact scheme

Pay 0.005 USDC on Base to 0x836B…19Ee2. The signed payment is good for 10 minutes.

USD Coin contract
0x8335…02913
Payment window
10 minutes
As published
5000 smallest units
The catalog’s raw entry
[
  {
    "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
    "extra": {
      "name": "USD Coin",
      "version": "2",
      "paymentFlow": "upfront",
      "resourceUrl": "https://api.magentlab.com/api/calc/improve_vte",
      "assetTransferMethod": "eip3009"
    },
    "payTo": "0x836Be278f1739fB4308091cD1852F7971Bc19Ee2",
    "amount": "5000",
    "scheme": "exact",
    "network": "eip155:8453",
    "maxTimeoutSeconds": 600
  }
]

Extensions

{
  "bazaar": {
    "info": {
      "input": {
        "body": {
          "items": [
            {
              "age": 50,
              "icu_ccu_stay": false,
              "previous_vte": false,
              "current_cancer": false,
              "known_thrombophilia": false,
              "lower_limb_paralysis": false,
              "immobilized_ge_7_days": false
            },
            {
              "age": 50,
              "icu_ccu_stay": false,
              "previous_vte": false,
              "current_cancer": false,
              "known_thrombophilia": false,
              "lower_limb_paralysis": false,
              "immobilized_ge_7_days": false
            }
          ]
        },
        "type": "http",
        "method": "POST"
      },
      "output": {
        "type": "json",
        "example": {
          "path": "/api/calc/improve_vte",
          "count": 2,
          "items": [
            {
              "score": 0,
              "formula": "improve_vte",
              "citation": {
                "id": "spyropoulos-2011",
                "doi": "10.1378/chest.10-1944",
                "pmid": "21436241",
                "title": "Predictive and associative models to identify hospitalized medical patients at risk for VTE",
                "source": "Chest. 2011;140(3):706-714",
                "authors": "Spyropoulos AC, Anderson FA Jr, FitzGerald G, Decousus H, Pini M, Chong BH, Zotz RB, Bergmann JF, Tapson VF, Froehlich JB, Monreal M, Merli GJ, Pavanello R, Turpie AGG, Nakamura M, Piovella F, Kakkar AK, Spencer FA, IMPROVE Investigators"
              },
              "vte_band": "0-1",
              "age_years": 50,
              "max_score": 12,
              "components": [
                {
                  "factor": "previous_vte",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "known_thrombophilia",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "lower_limb_paralysis",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "current_cancer",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "immobilized_ge_7_days",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "icu_ccu_stay",
                  "points": 0,
                  "present": false
                },
                {
                  "value": 50,
                  "factor": "age_gt_60",
                  "points": 0,
                  "present": false
                }
              ],
              "disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
              "formula_expression": "IMPROVE VTE (Spyropoulos 2011 7-factor associative during hospitalization) = previous_vte (3) + known_thrombophilia (2) + lower_limb_paralysis (2) + current_cancer (2) + immobilized_ge_7_days (1) + icu_ccu_stay (1) + age>60 (1); max 12; 0-1, 2-3 (observed VTE 1.5%), >=4 (observed VTE 5.7%); not the 4-factor admission predictive model; not IMPROVEDD"
            },
            {
              "score": 0,
              "formula": "improve_vte",
              "citation": {
                "id": "spyropoulos-2011",
                "doi": "10.1378/chest.10-1944",
                "pmid": "21436241",
                "title": "Predictive and associative models to identify hospitalized medical patients at risk for VTE",
                "source": "Chest. 2011;140(3):706-714",
                "authors": "Spyropoulos AC, Anderson FA Jr, FitzGerald G, Decousus H, Pini M, Chong BH, Zotz RB, Bergmann JF, Tapson VF, Froehlich JB, Monreal M, Merli GJ, Pavanello R, Turpie AGG, Nakamura M, Piovella F, Kakkar AK, Spencer FA, IMPROVE Investigators"
              },
              "vte_band": "0-1",
              "age_years": 50,
              "max_score": 12,
              "components": [
                {
                  "factor": "previous_vte",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "known_thrombophilia",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "lower_limb_paralysis",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "current_cancer",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "immobilized_ge_7_days",
                  "points": 0,
                  "present": false
                },
                {
                  "factor": "icu_ccu_stay",
                  "points": 0,
                  "present": false
                },
                {
                  "value": 50,
                  "factor": "age_gt_60",
                  "points": 0,
                  "present": false
                }
              ],
              "disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
              "formula_expression": "IMPROVE VTE (Spyropoulos 2011 7-factor associative during hospitalization) = previous_vte (3) + known_thrombophilia (2) + lower_limb_paralysis (2) + current_cancer (2) + immobilized_ge_7_days (1) + icu_ccu_stay (1) + age>60 (1); max 12; 0-1, 2-3 (observed VTE 1.5%), >=4 (observed VTE 5.7%); not the 4-factor admission predictive model; not IMPROVEDD"
            }
          ]
        }
      },
      "iconUrl": "https://api.magentlab.com/favicon.ico"
    },
    "schema": {
      "type": "object",
      "$schema": "https://json-schema.org/draft/2020-12/schema",
      "required": [
        "input"
      ],
      "properties": {
        "input": {
          "type": "object",
          "required": [
            "type",
            "method"
          ],
          "properties": {
            "body": {
              "type": "object",
              "required": [
                "items"
              ],
              "properties": {
                "items": {
                  "type": "array",
                  "items": {
                    "type": "object",
                    "required": [
                      "age",
                      "previous_vte",
                      "known_thrombophilia",
                      "lower_limb_paralysis",
                      "current_cancer",
                      "immobilized_ge_7_days",
                      "icu_ccu_stay"
                    ],
                    "properties": {
                      "age": {
                        "type": "integer",
                        "description": "Age in years (18-120). Scores 1 when age >60 (Spyropoulos 2011). Age 60 scores 0; age 61 scores 1."
                      },
                      "icu_ccu_stay": {
                        "type": "boolean",
                        "description": "ICU or CCU stay as assigned by the caller (Spyropoulos 2011, during hospitalization). true or false. 1 point if true. magent does not assign level of care."
                      },
                      "previous_vte": {
                        "type": "boolean",
                        "description": "Previous VTE as assigned by the caller (Spyropoulos 2011 7-factor associative model). true or false. 3 points if true. magent does not diagnose VTE."
                      },
                      "current_cancer": {
                        "type": "boolean",
                        "description": "Current cancer as assigned by the caller (Spyropoulos 2011). true or false. 2 points if true. magent does not diagnose cancer."
                      },
                      "known_thrombophilia": {
                        "type": "boolean",
                        "description": "Known thrombophilia as assigned by the caller (Spyropoulos 2011). true or false. 2 points if true. magent does not interpret a thrombophilia panel."
                      },
                      "lower_limb_paralysis": {
                        "type": "boolean",
                        "description": "Lower-limb paralysis as assigned by the caller (Spyropoulos 2011). true or false. 2 points if true. magent does not examine the patient."
                      },
                      "immobilized_ge_7_days": {
                        "type": "boolean",
                        "description": "Immobilized ≥7 days as assigned by the caller (Spyropoulos 2011, during hospitalization). true or false. 1 point if true. magent does not observe mobility."
                      }
                    }
                  },
                  "maxItems": 25,
                  "minItems": 1
                }
              },
              "additionalProperties": false
            },
            "type": {
              "type": "string",
              "const": "http"
            },
            "method": {
              "type": "string",
              "const": "POST"
            },
            "headers": {
              "type": "object",
              "additionalProperties": {
                "type": "string"
              }
            }
          },
          "additionalProperties": false
        },
        "output": {
          "type": "object",
          "required": [
            "type"
          ],
          "properties": {
            "type": {
              "type": "string"
            },
            "example": {
              "type": "object"
            }
          }
        }
      }
    }
  }
}

Provenance

Seen in the source catalog
2026-08-31 13:19Z
Last indexed by Roundhouse
2026-09-07 06:20Z
Last enriched (probe, favicon, geo)
2026-09-12 18:15Z
x402 version
2
Max timeout
600s
Liveness probe
HTTP 0
Report

Hand this page to an agent

Copy the prompt and paste it into Claude, an MCP client or your own agent — it will vet this service and call it over the free read API. No key, no account.

GET api.roundhouseai.io/v0/endpoints

This endpoint's own trailing-30-day call count, as published by the upstream catalog and snapshotted daily. 13 snapshots so far. Verified volume counts only settlements with an on-chain EIP-3009 marker.

Open skill.md
Show the prompt
Using Roundhouse, look up the x402 service magent and tell me whether it is
worth paying: what a call costs, whether the endpoint answered when last probed, and what
its payment record actually shows.

curl -s 'https://api.roundhouseai.io/v0/endpoints?q=magent'
curl -s 'https://api.roundhouseai.io/v0/merchants/<the payTo wallet returned above>'

Then call it: read the price from the live 402 at https://api.magentlab.com/api/calc/improve_vte, never from
a cached figure, and pay with an x402 client.

The /v0 API needs an API key (`authorization: Bearer rh_live_…`) on everything except
/v0/unified* and /v0/endpoints. Mint a personal key for $0.01 at GET https://api.roundhouseai.io/v0/test/x402,
or use an organization key from https://roundhouseai.io/dashboard/team.

If you do not have Roundhouse tools or skills installed, read
https://roundhouseai.io/skill.md first — it is the whole procedure.