Skip to main content
Glama

triage-mcp

An MCP server over my ai-triage-agent queue. A local LLM classifies support tickets and drafts replies, a human approves or rejects every one, and this server lets any MCP-capable AI client read that queue and the decision log.

It answers questions like "whats waiting for review?" or "what did I reject this week and why?" straight from the files the agent writes. Four tools, all read-only. The model can look at the queue but it cant approve, reject or send anything.

Tools

Tool

What it does

queue_status()

Counts for inbox, pending review by priority, outbox and logged decisions

pending_items(priority)

Tickets waiting for review, most urgent first, optional priority filter

recent_decisions(limit)

Latest human decisions from the audit log, newest first

search_decisions(query)

Search the decision log by id, outcome, category, priority or reject reason

Related MCP server: ticket-triage-mcp

Setup

python3 -m venv .venv
.venv/bin/pip install mcp

It reads ~/aiProjects/aminWork/automation-portfolio/ai-triage-agent/. Change DATA_DIR at the top of server.py if your copy lives somewhere else.

Wire it into Claude Code:

claude mcp add triage -- /path/to/triage-mcp/.venv/bin/python /path/to/triage-mcp/server.py

Demo

What it looks like from Claude Code:

> anything urgent sitting in the triage queue?

⏺ triage · pending_items()

  2 pending item(s):
  demo-014 P1 security_incident -> security-team (high): User entered their password on a fake helpdesk link and asks what to do next.
  demo-017 P3 software_issue -> service-desk (medium): Spreadsheet app crashes when opening one monthly report file.

⏺ One P1. demo-014 looks like a phishing hit and is routed to security.
  Id review that one first. The Excel crash can wait.

The tickets above are demo data. The format is exactly what the server returns.

Design notes

  • Read-only by construction. No tool writes to the queue, the outbox or the log. Approving stays in review.py with a human at the keyboard.

  • Only metadata crosses the protocol. Ticket bodies, extracted entities and reply text never leave the server. Summaries and reject reasons are cut to 100 characters with emails and home paths masked.

  • Small on purpose. One file, standard library plus the mcp SDK.

Honest notes

  • It only reads what ai-triage-agent has already written. With an empty pending/ folder most answers are zeros, which is normal between triage runs.

  • The masking is regex based. It catches emails and home paths, not names written into a summary.

  • All ticket content in the demo and the tests is made up. The logic is tested against a synthetic queue in test_server.py. Run python test_server.py.

About

Al Amin Bashir Afara, Dubai · github.com/aminafara123 · linkedin.com/in/aminafara

Related MCP Connectors

Related MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    Enables AI agents to audit and analyze Zendesk instances through a read-only MCP interface, providing tools for triggers, automations, analytics, and cross-reference queries.
    74
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI clients to perform safe, read-only IT diagnostics and retrieve local runbooks, asset records, and knowledge articles through MCP, with allowlisted network checks and audit logging.
    MIT
  • F
    license
    Not graded
    quality
    C
    maintenance
    Enables AI clients to access and manage an internal support ticket queue through MCP tools, resources, and prompts, including searching and viewing tickets, adding comments, closing tickets with confirmation, reading knowledge base articles, and viewing queue summaries over OAuth-secured Streamable HTTP.
    -