TicketDesk MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@TicketDesk MCPFind all open high-priority tickets and summarize their SLA status"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
TicketDesk MCP — Production-Style MCP Server & Client
A Model Context Protocol (MCP) server exposing an internal support-ticket queue, paired with a client that discovers and invokes its tools, resources, and prompts. Built for the "Build a Production MCP Server & Client" lab (Module 4, Model Context Protocol).
Contents
docs/tools-resources-prompts.md— what the server exposesdocs/architecture.md— transport choice & justificationdocs/security-summary.md— authentication, least privilege, error handlingdemo/session_log.txt— a real captured discovery-and-invocation run
Related MCP server: DeskCrew MCP Server
Architecture
flowchart TD
HOST["Host application\n(e.g. an AI assistant / chatbot)"] --> CLIENT
subgraph Client["client.py — fastmcp.Client"]
CLIENT["Discovery: list_tools / list_resources /\nlist_resource_templates / list_prompts"]
ELICIT["elicitation_handler\n(client-side safety gate for\nhigh-impact actions)"]
CLIENT <--> ELICIT
end
CLIENT <-->|"Streamable HTTP\nAuthorization: Bearer <token>"| SERVER
subgraph Server["server.py — FastMCP('TicketDesk')"]
AUTH["StaticTokenVerifier\n(read:tickets / write:tickets scopes)"]
TOOLS["Tools: search_tickets, get_ticket,\nadd_ticket_note, close_ticket"]
RES["Resources: ticket://{ticket_id},\npolicy://sla"]
PROMPT["Prompt: triage_ticket"]
AUTH --> TOOLS
AUTH --> RES
AUTH --> PROMPT
end
SERVER --> DATA[("data/tickets.json,\ndata/sla_policy.md")]Transport: Streamable HTTP — justified in docs/architecture.md
(short version: this is meant to be a shared internal capability multiple teams' AI
applications connect to, not a single local process pair, which is what stdio is suited
for).
What the server exposes
4 tools:
search_tickets,get_ticket,add_ticket_note,close_ticket(the last is a high-impact action gated by client-side elicitation)2 resources:
ticket://{ticket_id}(templated) andpolicy://sla(static)1 prompt:
triage_ticket
Full documentation of each: docs/tools-resources-prompts.md.
Setup & running the demo
pip install -r requirements.txt
# Terminal 1
python server.py
# Terminal 2
python client.py # interactive: real confirmation prompts via input()
python client.py --auto-confirm # non-interactive demo mode (used to produce demo/session_log.txt)client.py connects with dev-agent-token (read + write scopes), runs discovery, invokes
one of each tool/resource/prompt, demonstrates both error-handling failure modes
(Requirement 8), performs the high-impact close_ticket action through client-side
elicitation (Requirement 6), and finishes with a least-privilege demo showing
dev-readonly-token correctly rejected from a write-scoped tool.
Security
Full write-up: docs/security-summary.md. Short version:
bearer-token auth via StaticTokenVerifier, explicit per-tool scope checks (a real gap —
connection-level scope requirements alone do not restrict individual tool calls — was
found and fixed during development; see the security doc for the honest account), and
ToolError + mask_error_details=True to distinguish user-actionable errors from
internal failures that must never reach the client verbatim.
Requirements mapping
Requirement | Where it's satisfied |
≥3 tools |
|
≥2 resources, each a URI |
|
≥1 reusable prompt |
|
Client discovers + invokes each |
|
Transport choice justified |
|
Client-side safety feature | Elicitation gating |
Security design summary |
|
Error handling for a realistic failure mode | Invalid ticket ID ( |
Demonstration logs |
|
This server cannot be deployed
Maintenance
Related MCP Connectors
Helpdesk tickets from your AI: find, reply, take, hold, complete — within your own role. OAuth.
Build and manage AI-native customer support agents from Claude or any MCP client.
AI-native helpdesk hosted in Germany: tickets, replies, KPIs and knowledge base over MCP.
Customer support for MCP servers: work your tickets from Claude or any MCP client. Service key auth.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceEnables AI assistants to analyze IT support tickets, categorize urgency, suggest responses, and retrieve statistics via MCP tools.-
- AlicenseAqualityAmaintenanceEnables AI agents to perform helpdesk tasks over MCP, including ticket management, knowledge base search, and reply drafting, with optional pay-per-action USDC settlement and human approval workflows.232MIT
- FlicenseNot gradedqualityCmaintenanceEnables 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.-
- AlicenseNot gradedqualityBmaintenanceEnables an ElevenLabs support agent to call support tools over MCP, including Discord ticket flows, post-call webhook handling, and knowledge-base syncing.MIT