Senzing Entity Resolution

{
  "name": "Senzing Entity Resolution",
  "description": "Senzing entity resolution finds, deduplicates, links, and resolves person and organization records within and across data sources \u2014 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 \u2014 all from indexed documentation and code examples, no live Senzing instance needed. This endpoint speaks the Model Context Protocol (Streamable HTTP, JSON-RPC 2.0) \u2014 it is an MCP server, not an A2A message/send endpoint; connect with an MCP client.",
  "version": "1.39.4",
  "supportedInterfaces": [
    {
      "url": "https://mcp.senzing.com/mcp",
      "protocolBinding": "MCP",
      "protocolVersion": "1.0"
    }
  ],
  "provider": {
    "organization": "Senzing, Inc.",
    "url": "https://senzing.com"
  },
  "documentationUrl": "https://mcp.senzing.com/",
  "iconUrl": "https://mcp.senzing.com/favicon.ico",
  "capabilities": {
    "streaming": false,
    "pushNotifications": false,
    "extendedAgentCard": false
  },
  "securitySchemes": {},
  "securityRequirements": [],
  "defaultInputModes": [
    "text/plain",
    "application/json"
  ],
  "defaultOutputModes": [
    "text/plain",
    "application/json"
  ],
  "skills": [
    {
      "id": "data-mapping",
      "name": "Data Mapping",
      "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.",
      "tags": [
        "data-mapping",
        "entity-resolution",
        "etl",
        "json",
        "validation",
        "deduplication",
        "record-linkage"
      ],
      "examples": [
        "Map my customer CSV to Senzing format",
        "Help me map these source fields to entity resolution attributes",
        "Validate my Senzing JSON mapping"
      ]
    },
    {
      "id": "sdk-development",
      "name": "SDK Integration",
      "description": "Build entity resolution into your application. Scaffold working code, set up the SDK, and get API reference across Python, Java, and C# (official SDKs) plus Rust and TypeScript (community wrappers), on 5 platforms. Includes V3-to-V4 migration guidance for existing Senzing integrations.",
      "tags": [
        "sdk",
        "code-generation",
        "python",
        "java",
        "csharp",
        "rust",
        "typescript",
        "integration",
        "migration"
      ],
      "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": "documentation-search",
      "name": "Documentation & Examples",
      "description": "Find answers to Senzing entity resolution questions. Full-text search across indexed documentation and 53 GitHub repositories with real code examples for configuration, deployment, and API usage.",
      "tags": [
        "documentation",
        "search",
        "knowledge-base",
        "github",
        "examples",
        "configuration",
        "deployment"
      ],
      "examples": [
        "How do I configure Senzing for PostgreSQL?",
        "Find Python examples for entity search",
        "What are entity resolution principles?"
      ]
    },
    {
      "id": "error-troubleshooting",
      "name": "Error Troubleshooting",
      "description": "Diagnose and resolve Senzing errors. Look up 461 indexed error codes with root causes, resolution steps, and links to related documentation.",
      "tags": [
        "errors",
        "troubleshooting",
        "debugging",
        "diagnostics",
        "support"
      ],
      "examples": [
        "What does Senzing error 2089 mean?",
        "How do I fix SENZ-0033?"
      ]
    },
    {
      "id": "sample-data",
      "name": "Sample Data",
      "description": "Explore real-world entity resolution data to evaluate matching quality. CORD dataset records from Las Vegas, London, and Moscow, plus the Senzing demo truth set, with discovery and pagination.",
      "tags": [
        "sample-data",
        "cord",
        "testing",
        "entity-resolution",
        "datasets",
        "evaluation",
        "poc"
      ],
      "examples": [
        "Show me sample records from the Las Vegas dataset",
        "What sample data is available for testing?"
      ]
    },
    {
      "id": "reporting",
      "name": "Reporting & Analytics",
      "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.",
      "tags": [
        "reporting",
        "visualization",
        "analytics",
        "dashboard",
        "sql",
        "export",
        "data-quality"
      ],
      "examples": [
        "How do I export entity resolution results?",
        "Show me SQL queries for Senzing analytics",
        "Help me build a reporting dashboard"
      ]
    },
    {
      "id": "platform-engineering",
      "name": "Platform Engineering & Deployment",
      "description": "Design and operate Senzing in production. Cloud reference architectures (AWS, Azure, GCP), backing-database selection and sizing, replication and read replicas, high availability and failover, and infrastructure-as-code.",
      "tags": [
        "platform-engineering",
        "deployment",
        "cloud",
        "aws",
        "azure",
        "gcp",
        "kubernetes",
        "database",
        "replication",
        "high-availability",
        "terraform"
      ],
      "examples": [
        "Give me an AWS reference architecture for Senzing at 50M records",
        "Which database should I use and how do I size it?",
        "Design a highly-available deployment with read replicas"
      ]
    },
    {
      "id": "evaluation",
      "name": "Evaluation & Demos",
      "description": "Evaluate Senzing fast with no infrastructure. Build a quick local demo from your own data, run entity resolution on real sample data, and evaluate match quality on the free tier.",
      "tags": [
        "evaluation",
        "demo",
        "poc",
        "trial",
        "quickstart",
        "sample-data",
        "entity-resolution"
      ],
      "examples": [
        "Here's my customer CSV \u2014 build me a working demo I can show",
        "Load this sample data and show me the duplicates Senzing finds",
        "Help me evaluate resolution quality"
      ]
    }
  ]
}