zendesk-ops-mcp

An MCP server that provides operational tooling over the Zendesk Support API — ticket triage, SLA monitoring, agent workload analysis, and system health audits. Built for use with Claude Code or Claude Desktop, it gives support ops teams a conversational interface to automate the manual toil of managing Zendesk workflows.

Quick Start

git clone https://github.com/avg-ape/zendesk-ops-mcp.git
cd zendesk-ops-mcp
python3 -m venv .venv
source .venv/bin/activate
pip install -e .

Configure your Zendesk credentials:

cp .env.example .env
# Edit .env with your subdomain, email, and API token

You can get a free Zendesk trial at zendesk.com/register. Enable API tokens in Admin Center > Apps & Integrations > APIs.

Use with Claude Code

Add to your Claude Code MCP config (~/.claude/settings.json):

{
  "mcpServers": {
    "zendesk-ops": {
      "command": "/path/to/zendesk-ops-mcp/.venv/bin/python",
      "args": ["-m", "zendesk_ops_mcp.server"],
      "env": {
        "ZENDESK_SUBDOMAIN": "your-subdomain",
        "ZENDESK_EMAIL": "your-email@example.com",
        "ZENDESK_API_TOKEN": "your-api-token"
      }
    }
  }
}

Then ask Claude things like:

• "Triage open tickets — what's missing assignees or priorities?"

• "Show me tickets that have gone stale in the last 12 hours"

• "What's the CSAT score over the last 30 days, broken down by agent?"

• "Audit our macros — are there any duplicates or unused ones?"

• "Which agents are overloaded right now?"

Related MCP server: Zendesk API MCP Server

Tools

Architecture

Zendesk Client (zendesk_client.py): Async HTTP client built on httpx with Basic auth (API token). Handles both offset pagination (next_page) and cursor pagination for search endpoints. Rate limit tracking via X-RateLimit-Remaining headers.

Pydantic Models (models.py): All tool outputs are typed Pydantic models with human-readable __str__ methods. Claude gets structured data to reason about, not raw JSON.

Dual Pagination: Zendesk uses offset pagination for list endpoints (/api/v2/tickets.json) and search-specific pagination. The client handles both transparently via get_all() and search() methods.

Development

# Install with dev dependencies
pip install -e ".[dev]"

# Run unit tests
pytest tests/ -v

# Run integration tests (requires Zendesk credentials)
pytest tests/ -v --integration

License

MIT