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Fleetline

Command an agent fleet by voice. Fleetline is a self-hosted MCP server + Agent Skill that turns a voice assistant (Alexa+) into the operator of a local agent fleet: dispatch missions, watch workers execute in parallel, collect the report — hands-free.

Built for the Alexa+ track of the Amazon Build, Ship, Shape hackathon (2026), on the two open standards the track names: MCP Streamable HTTP transport (spec 2025-11-25) and Agent Skills.

 you (voice)          simulated Alexa+              Fleetline MCP server            agent fleet
 ──────────►  intent ────────────────► tools/call ───────────────────►  fetcher-01 ─┐
              (web app, per track     over Streamable HTTP              fetcher-02 ─┼─ parallel
               guidance for builders  POST /mcp + GET SSE               analyst-01 ─┘
               without device access)                                   composer-01 → report
                       ◄──────────── notifications/message ◄────────────  (live events)

What it does

  • 5 MCP tools (fleet_mission_submit, fleet_status, fleet_collect, fleet_cancel, fleet_roster) exposed over Streamable HTTP with stateful sessions, using the official TypeScript SDK.
  • A real fleet engine: role-specialized workers (4 fetchers, 3 analysts, 1 composer) run each mission as a parallel pipeline — fetch sources, analyze documents with local NLP (TF sentence ranking, keyword extraction, weighted toward the brief's subject terms so different briefs yield different reports), compose one report. Missions: briefing (research synthesis) and audit (source health). Zero paid APIs, zero API keys; runs entirely on your machine.
  • Live progress: every fleet state change streams to the client as an MCP notifications/message logging notification on the session's SSE stream.
  • Alexa+ web simulator (sanctioned by the track for builders without device access): a browser page that is itself a real MCP client — the official SDK client over Streamable HTTP — with an Alexa-style conversation pane, voice in/out (Web Speech API), and a live fleet dashboard. The interface ships one design system in two modes — Ops (default: dark, amber operations console) and Press (?theme=press: the light, paper-and-ink half of the same pair). Both modes are WCAG-contrast audited; video/README screenshots use the default.
  • Agent Skill (skills/fleet-operator/): standards-compliant SKILL.md packaging that teaches any Agent-Skills-compatible agent how to operate the fleet, with voice-shaped response guidance.

Quickstart

npm install
npm run build
npm start          # MCP endpoint at http://127.0.0.1:3000/mcp, simulator at http://127.0.0.1:3000/

Then, in a second terminal:

npm run demo       # CLI client: full mission lifecycle over Streamable HTTP

Or open http://127.0.0.1:3000/ and say "brief me on the AI news corpus". Append ?autodemo=1 to run one mission automatically (used in the demo video). The simulator works fully offline via a bundled corpus; pass real http(s) URLs as sources for live-network missions.

Official-tool check: npx @modelcontextprotocol/inspector --cli http://127.0.0.1:3000/mcp --method tools/list

Repository layout

Path What
src/index.ts HTTP server: MCP Streamable HTTP at /mcp (stateful sessions) + static simulator
src/mcp-server.ts Tool registrations + fleet-event → MCP notification bridge
src/fleet/ Fleet engine: manager, types, workers (fetch, analyze, compose), NLP, offline corpus
src/intents/router.ts Deterministic intent router standing in for the Alexa+ model in the simulator
public-src/simulator.ts, public/ The simulated Alexa+ experience (real SDK MCP client in the browser)
skills/fleet-operator/ Agent Skill (SKILL.md + operating guide reference)
scripts/demo-client.ts CLI proof client
test/ Unit + end-to-end tests (14)
proof/ Run artifacts: demo transcript, inspector output, live-URL audit, browser screenshot
demo/DEMO-SCRIPT.md Demo video script (~2:20, under the 2:30 cap; includes the cancel beat)
docs/FRICTION-LOG.md Product feedback on every tool used (track asks for this; up to 10% judging bonus)
SUBMISSION.md Paste-ready submission fields + the steps that need the operator

Verification

  • npm test — 14/14 green, including an end-to-end test that boots the real server and drives it with the official SDK client: initialize session, list tools, submit mission, receive fleet events as notifications, collect report, close session.
  • npm audit — 0 vulnerabilities.
  • proof/ — captured runs: CLI demo transcript, official MCP Inspector tools/list + tools/call, an audit mission against two live URLs, and a headless-Chrome screenshot of the simulator mid-mission.

Judging criterion map

Criterion Where Fleetline earns it
Tech Implementation Real MCP server on the official TS SDK with stateful Streamable HTTP sessions (spec 2025-11-25); a parallel worker-pool engine with a 3-stage task pipeline and survivable partial failure; server-initiated progress as MCP logging notifications; a browser MCP client built from the same SDK; 14 tests including a full end-to-end lifecycle; official MCP Inspector validation (proof/).
Design The simulator is a purpose-built voice-console: Alexa-style conversation pane with visible tool calls (honesty about what the assistant does), live fleet dashboard (roster, missions, event ticker) fed by the same notifications, one-glance quick-start chips, voice in/out. Voice-shaped replies (short, numbers-first) are codified in the Agent Skill.
Potential Impact One user, one workflow: the solo operator or developer running a local agent fleet who needs hands-free dispatch-and-collect — say "brief me on the AI news corpus" from across the room, come back to one finished report; keyboard-free and eyes-free, which is also the accessibility case (hands occupied, motor or visual constraints). Modeled on a real solo-operator workflow, not an enterprise category list. Beyond the hackathon, the audience is every developer already running local agents who wants voice as a second control surface — MCP is the portability layer, so Alexa+ operates the fleet today and any MCP client can tomorrow: no cloud, no keys, no per-call cost. And the strongest differentiator is true here: the track's sanctioned simulation path is exempt from runtime technology-hook requirements — Fleetline ships real runtime SDK hooks anyway (the simulator is itself an official-SDK MCP client over Streamable HTTP).
Quality of the Idea One idea carried all the way: your fleet, by voice. It inverts the usual "voice assistant as the agent" into "voice assistant as the fleet operator", and lands it on exactly the two standards the track names (MCP Streamable HTTP + Agent Skills), so the same fleet is operable by voice, CLI, or any MCP client.

Honest scope notes

  • The simulator's conversation brain is a deterministic intent router, not a large model — Alexa+ provides that model in production; the router stands in for it and is labeled as such in the UI. Everything else in the path (client, transport, tools, fleet, events) is real.
  • Workers run real but bounded work (HTTP fetch with timeout/size caps, local NLP, template composition). No LLM calls, no keys, no cloud, no cost.
  • Single-process, localhost-only, in-memory state. It is a demo-grade fleet, not a distributed orchestrator.

License

MIT — see LICENSE.

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Fleetline — command an agent fleet by voice (MCP + Agent Skills). Zero cloud, zero keys, deterministic.

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