# Senzing

> Use this tool when you need to resolve entity inconsistencies and errors in your data, and map disparate data sources to a unified view. Senzing solves problems of data duplication, inconsistencies, and errors by providing data mapping, SDK code generation, and error troubleshooting capabilities. It takes in disparate data sources as input and outputs a unified, accurate, and consistent entity view.

Canonical page: https://skillsregistry.net/skills/com-senzing-mcp  
JSON: https://api.skillsregistry.net/v1/skills/com-senzing-mcp

## Description

Entity resolution — data mapping, SDK code generation, docs search, and error troubleshooting

## Trust

- **Trust score (0–1):** 0.80
- **Verification tier:** unverified

## Facts

- **Version:** 0.13.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-07-16

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/com.senzing%2Fmcp)

## Use it

MCP endpoint published by the skill: `https://mcp.senzing.com/mcp`

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "com-senzing-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/com-senzing-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/com-senzing-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt