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: TicketAI
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 |
|
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