Afterglow
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., "@Afterglowplan a balanced $150 date night for two with different tastes"
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.
Afterglow
A date-night planner that makes room for two different tastes.
What works now
Choose up to five public cultural favorites per person
Set mood, start time and a $50–$250 sample budget for two
Generate a balanced dinner / activity / finale itinerary
Inspect the sample taste-fit explanation for each person
Swap stops without exceeding the original sample budget
Save and reopen nights on this browser, revise them, and export plain text
Inspect source/provenance and the explicit missing-integration state
Run the server-only Qloo integration against test fixtures
Connect a real external agent through MCP over stdio or stateless Streamable HTTP
The initial experience is a fictional sample. All sample places, prices and scores are hand-authored or calculated locally. There are no model calls, real reservations or Qloo calls in sample mode. The app never claims sample data is Qloo output.
Related MCP server: Nexxupp MCP Server
Run locally
Requires Node.js 24.x. Tested with Node.js 24.19.0.
npm ci --ignore-scripts
npm start
# http://localhost:4177No credentials are needed for the sample. The server does not automatically load .env files.
npm test
npm run check
npm run buildnpm test includes domain, HTTP, Qloo-adapter contract, MCP protocol and jsdom interaction tests. See verification for exact coverage and limits.
Design
Vanilla browser JavaScript, semantic HTML and responsive CSS keep the frontend small. Node's built-in HTTP server runs locally; Vercel function entrypoints are included under api/. There is no client framework, external font request, analytics, authentication database or model-provider requirement.
public/: interface, styling and fictional sample cataloglib/planner.mjs: validation, two-person ranking, budget-constrained route search and schedulinglib/qloo.mjs: pinned official Qloo harness bridge and live recommendation compositionlib/http.mjs: API handler, safe errors, payload limits and request gatelib/mcp.mjsandmcp-server.mjs: working agent-callable MCP toolsapi/: Vercel function entrypoints, including/api/mcptests/: test suitesdocs/: integration, release checklist and agent-tool contract
Recommendation approach
Sample mode turns hand-authored cultural tags into per-person fit indices. Afterglow gives 70% of the pair score to the lower score and 30% to the mean, then adds a small explicit mood preference. It evaluates every dinner/activity/finale combination within budget. This is an application ranking rule, not a probability of enjoyment.
Live mode asks Qloo separately for place recommendations using each person's chosen public cultural entity IDs. It intersects the results and balances their list-rank indices. It does not infer personal or sensitive traits. Qloo entity IDs, names and available raw affinities are retained separately from Afterglow's own indices and explanations.
Live mode produces a three-place discovery shortlist, not a verified dinner/activity/finale booking itinerary. It does not invent venue categories, prices, hours, available tables, opening times or travel durations. The budget is a restaurant price-tier filter; total live cost is unknown. Mood is displayed as the user's planning note and is not translated into unsupported Qloo parameters.
Live connection and release
Public production live access is blocked in code. Isolated stdio or protected-preview live tests require a durable ten-request maximum budget; see TEST_BUDGET.md. No real credential was read, copied, configured or used during this build. Follow INTEGRATION.md after the owner approves server-side credential configuration and a bounded live test. Never put keys in this repository, the browser or chat.
The public sample demo is deployed on Vercel. It is explicitly labeled fictional sample mode; see deployment verification. The protected-preview route is implemented but disabled until the shared durable quota store and Vercel Authentication are configured and verified. It has fixture coverage, not live Qloo proof. The SQLite test route does not make the hosted app live-ready. See the verification document for completed and pending checks.
Agentic tool interface
This project implements the competition’s agentic-tool route. A real MCP server exposes status, sample signals, Qloo entity search and constrained planning, plus a transparent planning prompt. An external agent can discover tools, search, call the planner, inspect the result and replan after user feedback. Both stdio and Streamable HTTP are tested with real MCP clients. See AGENT_INTEGRATION.md.
There is no bundled LLM and no autonomous in-app model loop. No model/provider is simulated. The sample UI alone is not evidence of a working Qloo-powered agent. Actual live Qloo execution from a chosen agent client is still required before claiming a competition-ready integration. No extra model API key is required by Afterglow; the agent host uses its own authorized model access.
Competition
Prepared for the Qloo Agentic Hackathon from original code. Official rules require actual Qloo integration, a functional accessible demo, public source and an open-source license. This local sample build is not submission-ready on its own. The source is available under the MIT license.
Dependency installation
Use the committed lockfile with npm ci --ignore-scripts. Scoped overrides pin brace-expansion 5.0.12 and undici 8.10.2 beneath pi-coding-agent 0.84.2. The root lock intentionally omits that package's hasShrinkwrap marker so npm installs the patched versions; regenerating the lock from scratch can restore the upstream versions. Verify actual installed package versions after dependency changes. The official Qloo harness remains pinned at 0.1.26.
This server cannot be deployed
Maintenance
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