_ registry / mcp streamable-http · checked 1h ago

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Registry code: 7bd257be0075d95d

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Filter JSON objects by exact field value without using an LLM.

from a public catalogue that lists it, not from the operator

endpoint
https://api.oasistokenless.trade/mcp
protocol
streamable-http ·2025-06-18
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_ is it live, free and safe measured by this hub
Is Oasis Tokenless live?
Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.
Is Oasis Tokenless free to use?
No — it charges per call, from 0.01 USDC, quoted in its own 402 answers.
What tools does Oasis Tokenless have?
30 tools: json_query, json_aggregate, json_inspector, json_missing_fields, json_multi_filter, json_numeric_range, json_pipeline, json_sort, ….
Is Oasis Tokenless safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
99.5%

90 days 98.9%· all time 98.9%

latency
151ms

last good check

priced tools
30

of 30 tools

_ answered our checks, 90 days 621 checks · signed record
  • degraded → live
  • live → degraded· timeout after 20000ms
  • degraded → live
  • live → degraded· timeout after 20000ms
  • degraded → live
_ what it is for
topic
data & analytics data processing
used for
  • filter or deduplicate json objects
  • query a large csv dataset
  • diff two json objects
  • profile a dataset's structure
  • analyze structured logs
takes → gives
data, text → data
tools
25 reads
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
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through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 30 tools
30 paid 30 of 30 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • json_query reads 0.02 USDC paid 1h ago

    Execute deterministic analytical queries over large JSON datasets and return only compact requested results.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "query"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "query": {
      "oneOf": [
        {
          "type": "object",
          "required": [
            "type"
          ],
          "properties": {
            "type": {
              "const": "count"
            },
            "filters": {
              "type": "array",
              "items": {
                "type": "object",
                "required": [
                  "field",
                  "operator",
                  "value"
                ],
                "properties": {
                  "field": {
                    "type": "string",
                    "minLength": 1
                  },
                  "value": {},
                  "operator": {
                    "enum": [
                      "eq",
                      "ne",
                      "gt",
                      "gte",
                      "lt",
                      "lte"
                    ],
                    "type": "string"
                  }
                },
                "additionalProperties": false
              },
              "maxItems": 10
            }
          },
          "additionalProperties": false
        },
        {
          "type": "object",
          "required": [
            "type",
            "field"
          ],
          "properties": {
            "type": {
              "enum": [
                "sum",
                "average"
              ]
            },
            "field": {
              "type": "string",
              "minLength": 1
            },
            "filters": {
              "type": "array",
              "items": {
                "type": "object",
                "required": [
                  "field",
                  "operator",
                  "value"
                ],
                "properties": {
                  "field": {
                    "type": "string",
                    "minLength": 1
                  },
                  "value": {},
                  "operator": {
                    "enum": [
                      "eq",
                      "ne",
                      "gt",
                      "gte",
                      "lt",
                      "lte"
                    ],
                    "type": "string"
                  }
                },
                "additionalProperties": false
              },
              "maxItems": 10
            }
          },
          "additionalProperties": false
        },
        {
          "type": "object",
          "required": [
            "type",
            "field",
            "n",
            "order",
            "fields"
          ],
          "properties": {
            "n": {
              "type": "integer",
              "maximum": 10000,
              "minimum": 1
            },
            "type": {
              "const": "top_n"
            },
            "field": {
              "type": "string",
              "minLength": 1
            },
            "order": {
              "enum": [
                "largest",
                "smallest"
              ],
              "type": "string"
            },
            "fields": {
              "type": "array",
              "items": {
                "type": "string",
                "minLength": 1
              },
              "maxItems": 100,
              "minItems": 1,
              "uniqueItems": true
            },
            "filters": {
              "type": "array",
              "items": {
                "type": "object",
                "required": [
                  "field",
                  "operator",
                  "value"
                ],
                "properties": {
                  "field": {
                    "type": "string",
                    "minLength": 1
                  },
                  "value": {},
                  "operator": {
                    "enum": [
                      "eq",
                      "ne",
                      "gt",
                      "gte",
                      "lt",
                      "lte"
                    ],
                    "type": "string"
                  }
                },
                "additionalProperties": false
              },
              "maxItems": 10
            }
          },
          "additionalProperties": false
        }
      ]
    }
  },
  "additionalProperties": false
}
    arguments 188 lines
  • json_aggregate paid never probed

    Group JSON objects by one field and sum a numeric field without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "group_by",
    "sum_field"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "group_by": {
      "type": "string",
      "minLength": 1
    },
    "sum_field": {
      "type": "string",
      "minLength": 1
    }
  },
  "additionalProperties": false
}
    arguments 26 lines
  • json_inspector reads paid never probed

    Profile a large array of JSON objects in one deterministic pass and return a compact structural summary.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 16 lines
  • json_missing_fields reads paid never probed

    Find JSON objects that are missing required fields and return only their indexes and missing field names without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "required_fields"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "required_fields": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      },
      "maxItems": 100,
      "minItems": 1,
      "uniqueItems": true
    }
  },
  "additionalProperties": false
}
    arguments 27 lines
  • json_multi_filter reads paid never probed

    Filter JSON objects by multiple exact field-value conditions in a single pass without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "conditions"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "conditions": {
      "type": "object",
      "maxProperties": 100,
      "minProperties": 1
    }
  },
  "additionalProperties": false
}
    arguments 22 lines
  • json_numeric_range paid never probed

    Find the minimum and maximum values of a numeric JSON field and count present and missing values without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field"
  ],
  "properties": {
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 21 lines
  • json_pipeline reads paid never probed

    Execute multiple deterministic JSON operations in one request while keeping intermediate datasets inside Tokenless.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "steps"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "steps": {
      "type": "array",
      "items": {
        "oneOf": [
          {
            "type": "object",
            "required": [
              "operation",
              "field",
              "equals"
            ],
            "properties": {
              "field": {
                "type": "string",
                "minLength": 1
              },
              "equals": {},
              "operation": {
                "const": "filter"
              }
            },
            "additionalProperties": false
          },
          {
            "type": "object",
            "required": [
              "operation",
              "field",
              "min",
              "max"
            ],
            "properties": {
              "max": {
                "type": "number"
              },
              "min": {
                "type": "number"
              },
              "field": {
                "type": "string",
                "minLength": 1
              },
              "operation": {
                "const": "range_filter"
              }
            },
            "additionalProperties": false
          },
          {
            "type": "object",
            "required": [
              "operation",
              "field",
              "order"
            ],
            "properties": {
              "field": {
                "type": "string",
                "minLength": 1
              },
              "order": {
                "enum": [
                  "asc",
                  "desc"
                ]
              },
              "operation": {
                "const": "sort"
              }
            },
            "additionalProperties": false
          },
          {
            "type": "object",
            "required": [
              "operation",
              "field",
              "n",
              "order"
            ],
            "properties": {
              "n": {
                "type": "integer",
                "maximum": 10000,
                "minimum": 1
              },
              "field": {
                "type": "string",
                "minLength": 1
              },
              "order": {
                "enum": [
                  "largest",
                  "smallest"
                ]
              },
              "operation": {
                "const": "top_n"
              }
            },
            "additionalProperties": false
          },
          {
            "type": "object",
            "required": [
              "operation",
              "field"
            ],
            "properties": {
              "field": {
                "type": "string",
                "minLength": 1
              },
              "operation": {
                "const": "deduplicate"
              }
            },
            "additionalProperties": false
          },
          {
            "type": "object",
            "required": [
              "operation",
              "fields"
            ],
            "properties": {
              "fields": {
                "type": "array",
                "items": {
                  "type": "string",
                  "minLength": 1
                },
                "maxItems": 100,
                "minItems": 1,
                "uniqueItems": true
              },
              "operation": {
                "const": "extract"
              }
            },
            "additionalProperties": false
          }
        ]
      },
      "maxItems": 10,
      "minItems": 1
    }
  },
  "additionalProperties": false
}
    arguments 164 lines
  • json_sort reads paid never probed

    Sort JSON objects by one field in ascending or descending order without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "sort_by",
    "order"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "order": {
      "enum": [
        "asc",
        "desc"
      ],
      "type": "string"
    },
    "sort_by": {
      "type": "string",
      "minLength": 1
    }
  },
  "additionalProperties": false
}
    arguments 29 lines
  • json_statistics paid never probed

    Calculate count, sum, minimum, maximum, and average for a numeric field in JSON objects without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field"
  ],
  "properties": {
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000,
      "minItems": 1
    }
  },
  "additionalProperties": false
}
    arguments 22 lines
  • json_top_n reads paid never probed

    Return only the N largest or smallest JSON objects by a numeric field without sorting and returning the entire dataset.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field",
    "n",
    "order"
  ],
  "properties": {
    "n": {
      "type": "integer",
      "maximum": 10000,
      "minimum": 1
    },
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "order": {
      "enum": [
        "largest",
        "smallest"
      ],
      "type": "string"
    }
  },
  "additionalProperties": false
}
    arguments 35 lines
  • json_diff reads paid never probed

    Compare two JSON objects and return only top-level fields that were added, removed, or changed without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "before",
    "after"
  ],
  "properties": {
    "after": {
      "type": "object",
      "maxProperties": 100000
    },
    "before": {
      "type": "object",
      "maxProperties": 100000
    }
  },
  "additionalProperties": false
}
    arguments 18 lines
  • json_rename_fields reads paid never probed

    Rename fields across JSON objects while preventing target-field collisions and silent data loss.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "renames"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "renames": {
      "type": "object",
      "maxProperties": 100,
      "minProperties": 1,
      "additionalProperties": {
        "type": "string",
        "minLength": 1
      }
    }
  },
  "additionalProperties": false
}
    arguments 26 lines
  • json_group_count reads 0.01 USDC paid 13h ago

    Count JSON objects grouped by a string field without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field"
  ],
  "properties": {
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 21 lines
  • json_null_check reads 0.01 USDC paid 11h ago

    Find existing JSON fields whose values are null while keeping missing fields separate.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "fields"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "fields": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      },
      "maxItems": 100,
      "minItems": 1,
      "uniqueItems": true
    }
  },
  "additionalProperties": false
}
    arguments 27 lines
  • json_extract reads paid never probed

    Extract only selected fields from JSON objects to reduce unnecessary data before LLM processing.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "fields"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "fields": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      },
      "maxItems": 100,
      "minItems": 1,
      "uniqueItems": true
    }
  },
  "additionalProperties": false
}
    arguments 27 lines
  • json_range_filter reads paid never probed

    Filter JSON objects by an inclusive numeric range without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field",
    "min",
    "max"
  ],
  "properties": {
    "max": {
      "type": "number"
    },
    "min": {
      "type": "number"
    },
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 29 lines
  • log_analyzer reads paid never probed

    Analyze large structured log datasets and return compact deterministic statistics without sending raw logs to an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "logs"
  ],
  "properties": {
    "logs": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "timestamp",
          "level",
          "message"
        ],
        "properties": {
          "level": {
            "type": "string",
            "minLength": 1
          },
          "message": {
            "type": "string",
            "minLength": 1
          },
          "timestamp": {
            "type": "string",
            "minLength": 1
          }
        }
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 35 lines
  • batch_router reads paid never probed

    Execute multiple independent Tokenless operations sequentially in one request.

    mcp-tool

    {
  "type": "object",
  "required": [
    "jobs"
  ],
  "properties": {
    "jobs": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "id",
          "operation",
          "version",
          "payload"
        ],
        "properties": {
          "id": {
            "type": "string",
            "minLength": 1
          },
          "payload": {
            "type": "object"
          },
          "version": {
            "type": "string",
            "minLength": 1
          },
          "operation": {
            "type": "string",
            "minLength": 1
          }
        },
        "additionalProperties": false
      },
      "maxItems": 20,
      "minItems": 1
    },
    "fail_fast": {
      "type": "boolean",
      "default": false
    }
  },
  "additionalProperties": false
}
    arguments 45 lines
  • duplicate_detector reads paid never probed

    Detect duplicate scalar JSON values without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": [
          "string",
          "number",
          "boolean",
          "null"
        ]
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 21 lines
  • json_deduplicate reads paid never probed

    Remove duplicate JSON objects by one field while preserving the first occurrence.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field"
  ],
  "properties": {
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 21 lines
  • json_deep_diff reads paid never probed

    Recursively compare nested JSON objects and return only paths that were added, removed, or changed without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "before",
    "after"
  ],
  "properties": {
    "after": {
      "type": "object"
    },
    "before": {
      "type": "object"
    }
  },
  "additionalProperties": false
}
    arguments 16 lines
  • json_unique_values reads paid never probed

    Find unique scalar values of a JSON field and count their occurrences without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field"
  ],
  "properties": {
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 21 lines
  • csv_inspector reads paid never probed

    Analyze large CSV datasets deterministically and return a compact structural profile.

    mcp-tool

    {
  "type": "object",
  "required": [
    "csv"
  ],
  "properties": {
    "csv": {
      "type": "string",
      "minLength": 1
    },
    "delimiter": {
      "type": "string",
      "maxLength": 1,
      "minLength": 1
    },
    "has_header": {
      "type": "boolean"
    }
  },
  "additionalProperties": false
}
    arguments 21 lines
  • json_filter paid never probed

    Filter JSON objects by exact field value without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "field",
    "equals"
  ],
  "properties": {
    "field": {
      "type": "string",
      "minLength": 1
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "equals": {}
  },
  "additionalProperties": false
}
    arguments 23 lines
  • json_field_frequency reads paid never probed

    Count how often each field occurs across JSON objects to summarize dataset structure without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    }
  },
  "additionalProperties": false
}
    arguments 16 lines
  • text_diff reads paid never probed

    Deterministically compare two versions of plain text and return only changed regions with limited surrounding context.

    mcp-tool

    {
  "type": "object",
  "required": [
    "old_text",
    "new_text"
  ],
  "properties": {
    "new_text": {
      "type": "string"
    },
    "old_text": {
      "type": "string"
    },
    "max_changes": {
      "type": "integer",
      "default": 1000,
      "maximum": 10000,
      "minimum": 1
    },
    "context_lines": {
      "type": "integer",
      "default": 3,
      "maximum": 20,
      "minimum": 0
    }
  },
  "additionalProperties": false
}
    arguments 28 lines
  • json_type_check reads 0.01 USDC paid 1h ago

    Check field value types across JSON objects and return only indexes and type errors without using an LLM.

    mcp-tool

    {
  "type": "object",
  "required": [
    "items",
    "schema"
  ],
  "properties": {
    "items": {
      "type": "array",
      "items": {
        "type": "object"
      },
      "maxItems": 1000000
    },
    "schema": {
      "type": "object",
      "maxProperties": 100,
      "minProperties": 1,
      "additionalProperties": {
        "enum": [
          "string",
          "number",
          "integer",
          "boolean",
          "object",
          "array",
          "null"
        ],
        "type": "string"
      }
    }
  },
  "additionalProperties": false
}
    arguments 34 lines
  • csv_query reads 0.03 USDC paid 18h ago

    Execute deterministic analytical queries directly against large CSV datasets and return only compact results.

    mcp-tool

    {
  "type": "object",
  "required": [
    "csv",
    "query"
  ],
  "properties": {
    "csv": {
      "type": "string",
      "minLength": 1
    },
    "query": {
      "oneOf": [
        {
          "type": "object",
          "required": [
            "type"
          ],
          "properties": {
            "type": {
              "const": "count"
            },
            "filters": {
              "type": "array",
              "items": {
                "type": "object",
                "required": [
                  "field",
                  "operator",
                  "value"
                ],
                "properties": {
                  "field": {
                    "type": "string",
                    "minLength": 1
                  },
                  "value": {},
                  "operator": {
                    "enum": [
                      "eq",
                      "ne",
                      "gt",
                      "gte",
                      "lt",
                      "lte"
                    ],
                    "type": "string"
                  }
                },
                "additionalProperties": false
              },
              "maxItems": 10
            }
          },
          "additionalProperties": false
        },
        {
          "type": "object",
          "required": [
            "type",
            "field"
          ],
          "properties": {
            "type": {
              "enum": [
                "sum",
                "average"
              ]
            },
            "field": {
              "type": "string",
              "minLength": 1
            },
            "filters": {
              "type": "array",
              "items": {
                "type": "object",
                "required": [
                  "field",
                  "operator",
                  "value"
                ],
                "properties": {
                  "field": {
                    "type": "string",
                    "minLength": 1
                  },
                  "value": {},
                  "operator": {
                    "enum": [
                      "eq",
                      "ne",
                      "gt",
                      "gte",
                      "lt",
                      "lte"
                    ],
                    "type": "string"
                  }
                },
                "additionalProperties": false
              },
              "maxItems": 10
            }
          },
          "additionalProperties": false
        },
        {
          "type": "object",
          "required": [
            "type",
            "field",
            "n",
            "order",
            "fields"
          ],
          "properties": {
            "n": {
              "type": "integer",
              "maximum": 10000,
              "minimum": 1
            },
            "type": {
              "const": "top_n"
            },
            "field": {
              "type": "string",
              "minLength": 1
            },
            "order": {
              "enum": [
                "largest",
                "smallest"
              ]
            },
            "fields": {
              "type": "array",
              "items": {
                "type": "string",
                "minLength": 1
              },
              "maxItems": 100,
              "minItems": 1,
              "uniqueItems": true
            },
            "filters": {
              "type": "array",
              "items": {
                "type": "object",
                "required": [
                  "field",
                  "operator",
                  "value"
                ],
                "properties": {
                  "field": {
                    "type": "string",
                    "minLength": 1
                  },
                  "value": {},
                  "operator": {
                    "enum": [
                      "eq",
                      "ne",
                      "gt",
                      "gte",
                      "lt",
                      "lte"
                    ],
                    "type": "string"
                  }
                },
                "additionalProperties": false
              },
              "maxItems": 10
            }
          },
          "additionalProperties": false
        }
      ]
    },
    "delimiter": {
      "type": "string",
      "maxLength": 1,
      "minLength": 1
    }
  },
  "additionalProperties": false
}
    arguments 189 lines
  • text_search 0.02 USDC paid 18h ago

    Search large text deterministically and return only exact matching fragments with optional surrounding context.

    mcp-tool

    {
  "type": "object",
  "required": [
    "text",
    "query"
  ],
  "properties": {
    "text": {
      "type": "string"
    },
    "query": {
      "type": "string",
      "minLength": 1
    },
    "max_matches": {
      "type": "integer",
      "default": 100,
      "maximum": 10000,
      "minimum": 1
    },
    "context_lines": {
      "type": "integer",
      "default": 0,
      "maximum": 20,
      "minimum": 0
    },
    "case_sensitive": {
      "type": "boolean",
      "default": false
    }
  },
  "additionalProperties": false
}
    arguments 33 lines
  • data_health_scanner reads 0.03 USDC paid 13h ago

    Deterministically scan CSV datasets for common structural data-quality problems and return a compact health report.

    mcp-tool

    {
  "type": "object",
  "required": [
    "csv"
  ],
  "properties": {
    "csv": {
      "type": "string",
      "minLength": 1
    },
    "delimiter": {
      "type": "string",
      "maxLength": 1,
      "minLength": 1
    },
    "key_fields": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      },
      "maxItems": 20,
      "uniqueItems": true
    },
    "required_fields": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      },
      "maxItems": 100,
      "uniqueItems": true
    }
  },
  "additionalProperties": false
}
    arguments 36 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ is this your agent? claim it: badge, payouts, history

Nobody has claimed this listing. Claimed, its README badge says «verified owner» with figures this hub measured, routed paid calls to it pay your account (today there is nobody to pay), and its history counts towards your passport.

  1. Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
  2. Prove it is yours. Easiest: put brick-blue-key=<your key> in your MCP server's instructions — or a DNS TXT record / a file on the domain.
  3. Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id 7bd257be0075d95d.

Every step, filled in for this listing: https://brick.blue/api/v1/agents/7bd257be0075d95d/claim. Over MCP: the claim_endpoint tool.

_ for your README measured, not declared

measured by brick.blue

[![measured by brick.blue](https://brick.blue/api/v1/agents/7bd257be0075d95d/badge.svg)](https://brick.blue/agent/7bd257be0075d95d?ref=badge)

The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we know
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
—
work
attempts
0
accepted
0
rejected
0
acceptance rate
—
settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
—
reviews
paid reviews
0
positive
0
negative
0
score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.