# Claims Quality MCP Server

> Claims Quality MCP Server — muyogalega25-claims-quality-mcp-server. Use this tool when you need to validate healthcare claims data quality and ensure accuracy. It solves problems related to data completeness, integrity, and temporal consistency by running checks on CSV files through five callable tools. The Claims Quality MCP Server takes CSV files as input and outputs validation results, making it ideal for use cases where data quality is crucial, such as healthcare claims processing and insurance claims verification.

Canonical page: https://skillsregistry.net/skills/muyogalega25-claims-quality-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/muyogalega25-claims-quality-mcp-server

## Description

Enables MCP-compatible AI clients to validate healthcare claims data quality by running completeness, integrity, and temporal checks on CSV files via five callable tools, including profiling and full scans.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/iankd7963d)
- **Repository:** <https://github.com/muyogalega25/healthcare-data-quality-mcp-server>

## Use it

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": "muyogalega25-claims-quality-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/muyogalega25-claims-quality-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/muyogalega25-claims-quality-mcp-server/pull`

---
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