{
  "capabilities": {
    "extendedAgentCard": false,
    "pushNotifications": false,
    "streaming": false
  },
  "defaultInputModes": [
    "text/plain",
    "application/json"
  ],
  "defaultOutputModes": [
    "text/plain",
    "application/json"
  ],
  "description": "Senzing entity resolution finds, deduplicates, links, and resolves person and organization records within and across data sources — building an identity-resolved graph with no model training required. Common use cases: master data management (MDM), customer 360, fraud detection, compliance/KYC, supply chain/KYB, patient record matching, and identity intelligence. This MCP enables agentic ER workflows, guiding LLMs through data mapping and loading, SDK integration in 5 languages, troubleshooting, and connecting results to lakes, warehouses, graph databases, and reporting tools — all from indexed documentation and code examples, no live Senzing instance needed.",
  "documentationUrl": "https://github.com/senzing-garage/sz-mcp-coworker",
  "name": "Senzing Entity Resolution",
  "provider": {
    "organization": "Senzing, Inc.",
    "url": "https://senzing.com"
  },
  "securityRequirements": [],
  "securitySchemes": {},
  "skills": [
    {
      "description": "Prepare source data for entity resolution so Senzing can match and link records. Interactive 8-step workflow: profile source fields, plan entity structure, map to Senzing attributes, generate validated JSON output, and optionally test with the SDK.",
      "examples": [
        "Map my customer CSV to Senzing format",
        "Help me map these source fields to entity resolution attributes",
        "Validate my Senzing JSON mapping"
      ],
      "id": "data-mapping",
      "name": "Data Mapping",
      "tags": [
        "data-mapping",
        "entity-resolution",
        "etl",
        "json",
        "validation",
        "deduplication",
        "record-linkage"
      ]
    },
    {
      "description": "Build entity resolution into your application. Scaffold working code, set up the SDK, and get API reference across Python, Java, C#, Rust, and TypeScript on 5 platforms. Includes V3-to-V4 migration guidance for existing Senzing integrations.",
      "examples": [
        "Generate Python code to initialize and load data with Senzing",
        "Set up the Senzing Java SDK on Docker",
        "How do I migrate from Senzing V3 to V4?"
      ],
      "id": "sdk-development",
      "name": "SDK Integration",
      "tags": [
        "sdk",
        "code-generation",
        "python",
        "java",
        "csharp",
        "rust",
        "typescript",
        "integration",
        "migration"
      ]
    },
    {
      "description": "Find answers to Senzing entity resolution questions. Full-text search across indexed documentation and 37 GitHub repositories with real code examples for configuration, deployment, and API usage.",
      "examples": [
        "How do I configure Senzing for PostgreSQL?",
        "Find Python examples for entity search",
        "What are entity resolution principles?"
      ],
      "id": "documentation-search",
      "name": "Documentation & Examples",
      "tags": [
        "documentation",
        "search",
        "knowledge-base",
        "github",
        "examples",
        "configuration",
        "deployment"
      ]
    },
    {
      "description": "Diagnose and resolve Senzing errors. Look up 456 indexed error codes with root causes, resolution steps, and links to related documentation.",
      "examples": [
        "What does Senzing error 2089 mean?",
        "How do I fix SENZ-0033?"
      ],
      "id": "error-troubleshooting",
      "name": "Error Troubleshooting",
      "tags": [
        "errors",
        "troubleshooting",
        "debugging",
        "diagnostics",
        "support"
      ]
    },
    {
      "description": "Explore real-world entity resolution data to evaluate matching quality. CORD dataset records from Las Vegas (265K+ records), London, and Moscow with discovery and pagination.",
      "examples": [
        "Show me sample records from the Las Vegas dataset",
        "What sample data is available for testing?"
      ],
      "id": "sample-data",
      "name": "Sample Data",
      "tags": [
        "sample-data",
        "cord",
        "testing",
        "entity-resolution",
        "datasets",
        "evaluation",
        "poc"
      ]
    },
    {
      "description": "Extract insights from entity resolution results. SDK patterns for data export, SQL analytics queries, data mart schemas, dashboard design, and resolution quality evaluation across 5 languages.",
      "examples": [
        "How do I export entity resolution results?",
        "Show me SQL queries for Senzing analytics",
        "Help me build a reporting dashboard"
      ],
      "id": "reporting",
      "name": "Reporting & Analytics",
      "tags": [
        "reporting",
        "visualization",
        "analytics",
        "dashboard",
        "sql",
        "export",
        "data-quality"
      ]
    }
  ],
  "supportedInterfaces": [
    {
      "protocolBinding": "jsonrpc",
      "protocolVersion": "2024-11-05",
      "url": "https://mcp.senzing.com/mcp"
    }
  ],
  "version": "1.13.4"
}