vexa
Vexa-ai · Vexa-ai/vexa
An MCP server that provides real-time, speaker-attributed meeting transcripts from Google Meet, Teams, and Zoom for AI agents to process.
Open-source meeting transcription API for Google Meet, Microsoft Teams & Zoom. Auto-join bots, real-time WebSocket transcripts, MCP server for AI agents. Self-host or use hosted SaaS.
Preview
What you can do with it
- Get real-time transcripts of virtual meetings to summarize key discussion points.
- Feed meeting discussions to an AI agent to build a collaborative knowledge base.
- Analyze meeting content to identify action items or decisions made.
Safety check
Usable, but read the notes first.
- ●Mentions credential files (SSH keys, cloud or npm tokens).
clients/claude-plugin/skills/setup/SKILL.md
Automated scan of the repo files. Always review code you run.
From the README
Vexa
Open-source meeting bots and real-time transcription — cloud or fully self-hosted.
A bot joins your Google Meet, Microsoft Teams, and Zoom calls and streams speaker-attributed transcripts in real time — through our API or one you host — then feeds sandboxed agents that build a Markdown knowledge base your team owns. Apache-2.0, air-gap-ready. (Jitsi: join + capture offline-proven, live validation pending — #883.)
vexa.ai runs Vexa 0.12 for meeting bots and transcription. Sandboxed knowledge agents are self-hosted only — self-host Vexa to run the full stack.
Connect your agent · Get an API key · Talk to the founder
Why Vexa
Every meeting-AI tool you can buy sends your conversations to their cloud and rents you access back. Vexa inverts that: run the stack yourself, point it at your own models, own what your meetings become.
No one else has all three:
-
Vexa is in the meeting. A real bot joins Meet, Teams and Zoom — Jitsi offline-proven, live validation pending — and streams speaker-attributed transcripts live. That bot fleet is the genuinely hard part — every "chat with your docs" tool starts after a transcript exists. Vexa produces it.
-
Your knowledge is files you own. Meetings compile into Markdown in a git repo — portable, diffable, greppable. Knowledge as code.
-
Agents work it, safely. Sandboxed coding agents read and write that repo like developers — isolated ephemeral containers, no egress, thousands in parallel, on Docker or your Kubernetes.
Only here for the transcription API? It's a complete standalone product — send a bot, read the stream, ignore the agent lane entirely.
⚡ Quickstart
Just want a bot in a meeting? Use the hosted service — no install. Sign in at vexa.ai/signin, copy your key from your account page, and send a bot:
curl -X POST "https://api.cloud.vexa.ai/bots" \
-H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
-d '{"platform":"google_meet","native_meeting_id":"abc-defg-hij","bot_name":"Vexa"}'
New accounts get $2 of free bot credit, no card required — about 6 hours of bot time at $0.30/hr (pricing). More calls: Send a bot.
Or self-host the whole stack
That is also how you get the agent plane, which is not part of the hosted service. Self-host on one host, then explore it in the Terminal or drive it over the API. Linux (Ubuntu 24.04) is the production target; a Mac with Docker Desktop works fine for a local evaluation — everything runs in containers either way.
Prerequisites — make, Docker engine ≥ v26 (make all checks), and transcription: a free token at
vexa.ai/account, or self-host the (GPU) transcription unit for a fully
air-gapped setup. By default POST /bots requires STT and answers 503 when it is missing
(make all warns when the credentials block in .env is empty). Capture-only is an explicit opt-out:
{"transcribe_enabled": false} on the spawn (or set TRANSCRIBE_ENABLED=false for the deployment).
Build machine:
make allpulls the published, release-validated images — no build, so a modest box is fine.make lite(the single-container all-in-one image) is lighter still. Building from this checkout instead (make dev, for contributors) wants 8 vCPUs and 16 GB RAM.
git clone https://github.com/Vexa-ai/vexa.git && cd vexa
make all # full Docker Compose stack — seeds .env, pulls the images (bot included),
# prints your API key + URLs. Contributors: `make dev` builds from this checkout.
When make all finishes it prints your key and URLs:
Terminal UI : http://localhost:13000 # the web workbench
API gateway : http://localhost:18056 # the API
API key : vxa_…
Explore in the Terminal (the fast path)
The Terminal is the way to see what Vexa can do. Open http://localhost:13000 — you're
already signed in to a self-host account. From the
workbench you can, with no curl:
- Send a bot — paste a Meet / Zoom / Teams / Jitsi URL; a bot joins as a participant.
- Watch the transcript stream in live, speaker-attributed, draft-then-confirmed.
- Chat with your workspace — ask an agent that has every captured meeting as context, and watch it commit what you decide.
Or drive it over the API
export API_KEY=vxa_...
export API_BASE=http://localhost:18056
# WIN 1 — send a bot into a live call, then read the transcript as it streams
curl -X POST "$API_BASE/bots" \
-H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
-d '{"platform":"google_meet","native_meeting_id":"abc-defg-hij","bot_name":"Vexa"}'
curl -H "X-API-Key: $API_KEY" "$API_BASE/transcripts/google_meet/abc-defg-hij"
# WIN 2 — ask an agent that has your whole workspace as context (answer streams back as SSE)
curl -N -X POST "$API_BASE/agent/chat" \
-H "X-API-Key: $API_KEY" -H "Content-Type: application/json" \
-d '{"prompt":"What did we decide in my last meeting?"}'
platform is google_meet · teams · zoom · jitsi; native_meeting_id is the code from the join URL. The
agent reply streams as Server-Sent Events — message-delta frames carry the text, commit frames mark
anything it recorded into your workspace.
🧩 How it works
One gateway, two domains — Meetings (capture) and Agents (work the knowledge) — both running on the same runtime: the engine that spawns every bot and every agent in its own sandboxed container.
A bot and an agent are the same runtime.v1 workload