BountyPilot
Provides an Alexa+ integration surface over MCP, exposing BountyPilot's tools for analyzing opportunities, saving them to a queue, comparing opportunities, building submission plans, tracking status, and asking for the next best action.
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., "@BountyPilotanalyze this bounty opportunity and save it to my queue"
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.
BountyPilot
BountyPilot is a self-hosted Model Context Protocol server plus a web-based Alexa+ simulation built for the Amazon Developer Hackathon 2026 — Alexa+ track.
It turns bounty hunting into a stateful agent workflow instead of a one-shot Q&A:
analyze an opportunity against an async, code-first profile;
save it to a persistent queue;
compare opportunities without hiding blockers;
build a concrete submission plan;
track progress across sessions;
ask for the next best action;
get a daily priority briefing across the active queue.
The simulator invokes the same eight MCP tools through the official SDK using an in-memory MCP transport. The separately exposed /mcp route serves the same tool surface over Streamable HTTP for external clients and Alexa+ integration.
The Alexa+ simulation
The web simulator is a multi-turn conversation, not a form:
"Alexa, open BountyPilot" — on a returning visit it greets you with your saved pipeline and the next step.
Attach a listing and ask "is this worth building?" — it analyzes, saves, and (for SKIP) files the listing as skipped on its own, then tells you what to do next.
"What should I work on today?", "What's in my queue?", "Plan my top opportunity", "I submitted it" — each maps to a short chain of MCP tool calls.
Replies are read aloud with the browser's built-in speech synthesis (toggle in the header), and results come back as cards: a verdict card, a daily briefing card, a plan card, and a queue carousel. Every turn shows the MCP tool calls it made.
Intent routing (src/conversation.js) is rule-based on purpose: every decision is explainable and the demo needs no paid model API.
Related MCP server: Decepticon
Track technology
Self-hosted MCP server
Streamable HTTP endpoint:
/mcpMCP TypeScript SDK v2
Verified negotiated protocol version:
2026-07-28(newer than the hackathon minimum2025-11-25)Web simulator uses an MCP client over the SDK's in-memory transport; it does not bypass the MCP tool layer
Public
/mcpuses Streamable HTTP and exposes the same eight tools
Run
npm install
npm startOpen http://127.0.0.1:4310.
Verify MCP
With the server running:
npm run smokeThe smoke client performs a real initialize handshake, requires the full eight-tool surface, calls analyze_opportunity and daily_briefing, and exits non-zero if protocol/tool/runtime checks fail.
Tools
analyze_opportunitysave_opportunityget_opportunity_queuecompare_opportunitiesbuild_submission_planset_opportunity_statusdaily_briefingnext_best_action
State
Each browser gets its own workspace id (kept in localStorage), so visitors never see each other's queue. External MCP clients pass an optional workspace argument; without it they use default.
Storage is chosen from the environment, in this order:
Environment | Storage | Survives restarts |
| Redis over REST | yes |
| that file | yes |
running on Vercel with neither | function | no — may reset on a cold start |
local default |
| yes |
GET /health reports which one is active, and the simulator shows it in the header. Files written by v0.1 (a single top-level queue) are read as the default workspace.
Privacy and cost
The current proof of concept uses no paid model API and sends no listing text to a third-party model. State is local to the self-hosted server.
License
MIT.
This server cannot be deployed
Maintenance
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AI workflow/MCP implementation package planner.
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