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Alexa Language Bridge

by kishormorol
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TypeScript
Hybrid

Alexa Language Bridge

An Alexa+ MCP add-on that gives a household member who does not speak English the run of the house.

Not a translator. Ma adds rice to the shopping list in Bangla and her son reads it in English. She ticks off the milk he added. She sets him a reminder, turns off the kitchen light, leaves him a message that arrives in his language when he next asks. The device stops being an English appliance the family operates on her behalf and becomes one she uses herself.

Nothing in the house is stored in English and translated for her. Everything is stored as spoken, and rendered for whoever is asking.

Script is part of who a person is, not something to guess per message. Plenty of people speak Bangla or Hindi and read it in Latin letters — bati, not বাতি. Get that wrong and the reply is one they cannot read, or match against what they said.

Status: early development. Built for the Build, Ship, Shape: Amazon Developer Hackathon (Alexa+ track), submission window 31 Aug – 23 Oct 2026.

How it works

Piece

What it does

MCP server

Streamable HTTP, MCP spec 2025-11-25

Auth

OAuth 2.1 authorization code + PKCE (S256)

Language layer

Renders any stored utterance into the asker's language, cached

State

Members, languages, lists, reminders, devices and messages, across sessions

Surface

MCP App card showing both languages side by side

Related MCP server: langlearn-tts

Setup

Requires Node 24 or newer. No cloud account is needed to run or test this — the default language provider runs offline.

git clone https://github.com/kishormorol/alexa-language-bridge.git
cd alexa-language-bridge
npm install
cp .env.example .env
npm run dev

The MCP endpoint is then at http://127.0.0.1:3000/mcp, with a liveness probe at /healthz.

npm test         # unit tests plus an end-to-end MCP client/server round trip
npm run build    # compile to dist/
npm start        # run the compiled server

The simulator

The hackathon rules accept a simulated Alexa+ experience, and the real MCP Toolkit is gated behind Amazon onboarding this project does not have (FL-003). So the demo surface is our own host:

npm run sim     # then open http://localhost:4000

One command boots the MCP server with OAuth enforced, walks the full authorization code + PKCE flow as a real client would, connects over Streamable HTTP, and serves a screen. Pick who is speaking, say something, watch the tool call and the card.

It is a genuine MCP host — it authenticates properly, reads tools/list, honours the _meta.ui.resourceUri a tool declares, and fetches the ui:// resource to render. Nothing is stubbed between the UI and the server.

Intent routing stands in for what Alexa+ would do. ROUTER=rules is deterministic and offline; a Bedrock-backed router replaces it once model access lands.

Authentication

OAuth 2.1 authorization code with PKCE (S256), enforced by default.

Unauthenticated POST /mcp

401 with a WWW-Authenticate challenge naming the resource metadata

Authorization server metadata

/.well-known/oauth-authorization-server

Protected resource metadata

/.well-known/oauth-protected-resource/mcp

Client registration

Dynamic (RFC 7591) at /register

Resource indicators

RFC 8707 — resource required on authorize and token, and tokens are bound to it

Authorization codes are single-use and expire in 60 seconds; access tokens last an hour and carry the resource they were issued for. There is no consent screen — authorize approves immediately, which is the one piece a real deployment would replace.

Set AUTH_ENABLED=false for local iteration only.

Tools

People

Tool

What it does

register_household_member

Record a person, the language they speak, and the script they write it in

list_household_members

Who is in the household, and in what language

Getting things done

Tool

What it does

add_to_list

Add to a shared list, in your own words

read_list

Read the list back in the asker's language

complete_list_item

Tick off an item, matched in any language it is held in

set_reminder

Set a reminder for yourself or someone else

get_reminders

What is waiting, in your own language

register_device

Name something controllable, in your own words

set_device_state

Turn it on or off, by whatever you call it

Talking to each other

Tool

What it does

leave_message

Store a spoken message, delivered in the recipient's language

get_messages

Read back waiting messages in the reader's own language

interpret_for_household

Carry a live utterance from one person's language to another's

The card

interpret_for_household and read_list carry an MCP Apps UI: a ui:// resource served as text/html;profile=mcp-app, showing what was said and what the other person hears side by side, never one translated into the other.

The official @modelcontextprotocol/ext-apps package targets the v2 SDK line and zod 4, which is incompatible with the 1.x line where the Streamable HTTP transport lives — so the contract is implemented directly. See FL-005.

Language provider

Two implementations behind one interface:

LANGUAGE_PROVIDER

Behaviour

echo (default)

Offline. Does not translate — prefixes text with the target tag, so a wrong-language rendering is obvious rather than silently plausible.

bedrock

Claude on Amazon Bedrock via the Mantle client. Frozen, cached system prompt and effort: low, both for the 500 ms round-trip budget.

Switching is one environment variable; nothing outside src/lang/ changes.

LANGUAGE_PROVIDER=bedrock AWS_PROFILE=alexa-hackathon npm run sim

A content-addressed cache sits in front of whichever provider is active. A household repeats itself — the same groceries, the same reminders — so most turns never reach the model. Identical concurrent misses share one in-flight call, and a cache hit does no disk write, because that is the hot path of a 500 ms budget.

npm run bench                 # cold vs warm round-trip latency
PREWARM=true npm run sim      # warm the common phrases at startup

p50

A phrase the household has said before

~5 ms

A phrase nobody has said before

~650 ms

The 500 ms budget is met for repeats and missed for novel utterances. Pre-warming covers the phrases a kitchen actually repeats; it cannot cover every sentence, and the numbers above say so rather than quoting the flattering one.

Server overhead measured at 1–3 ms per tool round trip, so effectively the whole budget is available to the model. Deployment notes: docs/deployment.md.

Repository layout

src/          MCP server, tools, auth, MCP App UI
docs/         design notes and decisions
PLAN.md       build plan and milestones
FRICTION.md   running friction log
PRODUCT-FEEDBACK.md   submission feedback answers

License

MIT — see LICENSE.

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

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