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SeedBase Test Data

Generate realistic, FK-consistent synthetic test data for your databases from your AI assistant.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
97%
Vollständigkeit des Schemas
88%
Qualität der Benennung
100%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
90%
Einhaltung des Protokolls
100%

Befunde (1)

  • LOWTool 'fetch_generation' suggests web access but openWorldHint=falsein fetch_generation

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~1,284Tokens (Tool-Definitionen)
~1.8 KBTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (1.00% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "seedbase": {
      "command": "npx",
      "args": [
        "@seedbase/client"
      ]
    }
  }
}

Ausführbare Pakete

npm@seedbase/client0.2.2stdio

Remote-Endpunkte

https://seedba.se/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (6)

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🟢list_projects

List your SeedBase projects (id, name, database type). Use this first to find the project to work with.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "projects": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string"
          },
          "name": {
            "type": "string"
          },
          "db_type": {
            "type": "string"
          }
        },
        "required": [
          "id",
          "name",
          "db_type"
        ]
      }
    }
  },
  "required": [
    "projects"
  ]
}
🟢get_ddl(project, dialect)

Get a project's schema as CREATE TABLE statements. Accepts a project id or name and an optional SQL dialect (postgresql, mysql, sqlite, mssql).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "project": {
      "type": "string",
      "description": "Project id (UUID) or project name"
    },
    "dialect": {
      "type": "string",
      "enum": [
        "postgresql",
        "mysql",
        "sqlite",
        "mssql"
      ],
      "description": "SQL dialect for the DDL (default: the project's database type)"
    }
  },
  "required": [
    "project"
  ],
  "additionalProperties": false
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "ddl": {
      "type": "string"
    },
    "dialect": {
      "type": "string"
    }
  },
  "required": [
    "ddl",
    "dialect"
  ]
}
🟡generate_test_data(project, rows, seed)

Generate a fresh synthetic dataset for a project and return it as SQL INSERT statements. Optionally set rows per table. The data is foreign-key consistent.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "project": {
      "type": "string",
      "description": "Project id (UUID) or project name"
    },
    "rows": {
      "type": "integer",
      "minimum": 1,
      "description": "Rows per table (optional; plan limits apply)"
    },
    "seed": {
      "type": "integer",
      "description": "Seed for deterministic output (optional)"
    }
  },
  "required": [
    "project"
  ],
  "additionalProperties": false
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "status": {
      "type": "string",
      "enum": [
        "completed",
        "running"
      ]
    },
    "generation_id": {
      "type": "string"
    },
    "sql": {
      "type": "string",
      "description": "Complete SQL INSERTs. Absent when the result is too large — download it from download_url instead; no partial SQL is ever returned."
    },
    "truncated": {
      "type": "boolean",
      "description": "True when the SQL was too large to inline. The response then contains NO sql; fetch the complete file from download_url."
    },
    "download_url": {
      "type": "string",
      "description": "Authenticated download endpoint for the complete SQL (send your API key as 'Authorization: Bearer …')."
    },
    "sql_chars": {
      "type": "integer"
    }
  },
  "required": [
    "status",
    "generation_id"
  ]
}
🟢fetch_generation(generation_id)

Fetch a previously started generation by id: returns its status, and the SQL INSERT statements once completed. Use this when generate_test_data reported the generation as still running.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "generation_id": {
      "type": "string",
      "description": "The generation id (UUID) reported by generate_test_data"
    }
  },
  "required": [
    "generation_id"
  ],
  "additionalProperties": false
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "status": {
      "type": "string",
      "enum": [
        "completed",
        "running"
      ]
    },
    "generation_id": {
      "type": "string"
    },
    "sql": {
      "type": "string",
      "description": "Complete SQL INSERTs. Absent when the result is too large — download it from download_url instead; no partial SQL is ever returned."
    },
    "truncated": {
      "type": "boolean",
      "description": "True when the SQL was too large to inline. The response then contains NO sql; fetch the complete file from download_url."
    },
    "download_url": {
      "type": "string",
      "description": "Authenticated download endpoint for the complete SQL (send your API key as 'Authorization: Bearer …')."
    },
    "sql_chars": {
      "type": "integer"
    }
  },
  "required": [
    "status",
    "generation_id"
  ]
}
🟡create_project(name, db_type)

Create a new, empty SeedBase project. Use import_schema afterwards to add the schema.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Project name"
    },
    "db_type": {
      "type": "string",
      "enum": [
        "postgresql",
        "mysql",
        "sqlite",
        "mssql"
      ],
      "description": "Target database type (default: postgresql)"
    }
  },
  "required": [
    "name"
  ],
  "additionalProperties": false
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string"
    },
    "name": {
      "type": "string"
    },
    "db_type": {
      "type": "string"
    }
  },
  "required": [
    "id",
    "name",
    "db_type"
  ]
}
🔴import_schema(project, content, format)

Import a database schema into a project from pasted content: SQL DDL (CREATE TABLE …, raw pg_dump/mysqldump schema output works), SQL INSERT dumps, CSV/TSV, JSON, or ORM model code (Django, Prisma, SQLAlchemy, …). Replaces the project's current schema.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "project": {
      "type": "string",
      "description": "Project id (UUID) or project name"
    },
    "content": {
      "type": "string",
      "description": "The schema source text (e.g. the DDL)"
    },
    "format": {
      "type": "string",
      "description": "Optional hint: sql, csv, tsv, json, or an ORM name (django, prisma, sqlalchemy, …). Auto-detected when omitted."
    }
  },
  "required": [
    "project",
    "content"
  ],
  "additionalProperties": false
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "table_count": {
      "type": "integer"
    },
    "fk_count": {
      "type": "integer"
    },
    "tables": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "warnings": {
      "type": "array",
      "items": {
        "type": "string"
      }
    }
  },
  "required": [
    "table_count",
    "fk_count"
  ]
}

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