# Customer Support Analyst MCP

> Customer Support Analyst MCP — zivsapir-customer-support-analyst-mcp. Use this tool when you need to analyze and respond to customer support tickets using natural-language queries. It solves problems related to efficient ticket management, such as quickly identifying patterns and trends, and provides inputs including ticket data and outputs like grouped ticket counts and relevant search results. Ideal for use in customer support environments where fast and accurate information retrieval is crucial.

Canonical page: https://skillsregistry.net/skills/zivsapir-customer-support-analyst-mcp  
JSON: https://api.skillsregistry.net/v1/skills/zivsapir-customer-support-analyst-mcp

## Description

Enables natural-language Q&A over customer support ticket data. Provides tools for schema inspection, SQL-based ticket counts and grouping, and full-text search for customer wording without requiring API keys.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/r8m6rvgzwp)
- **Repository:** <https://github.com/ZivSapir/customer-support-analyst-mcp>

## 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": "zivsapir-customer-support-analyst-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zivsapir-customer-support-analyst-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zivsapir-customer-support-analyst-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