
call4me
io.github.skeptrunedevv1.0.0Updated Oct 1, 2026
An AI agent that makes phone calls for you: bookings, appointments, cancellations.
Overview
Lets an AI assistant place real phone calls to businesses for bookings, appointments, and cancellations.
- What it does
- call4me gives a coding agent one new tool: make a phone call. The agent hands a task to a voice worker that dials a business over the phone network and holds a live spoken conversation, using back-office functions to end the call, ask the user something, or press keypad digits. It also exposes a tool to fetch recordings of finished calls, and a call page shows status and transcripts.
- When to use it
- Use it when you want an assistant to handle routine phone errands such as booking, rescheduling, or cancelling appointments, or to retrieve recordings of calls it made. It is aimed at users who would rather delegate a short business call than dial it themselves.
- Requirements
- A remote MCP endpoint at call4.me; no local runtime or package is needed. Access is prepaid: credits start at $10 via Stripe Checkout and reload monthly by default, and the MCP URL carries the account key. Self-hosting instead needs a Telnyx Call Control application and API key, an OpenAI API key with GPT-Live access, Stripe webhooks, and Cloudflare Workers with a D1 database.
Installation
In SourceWeft
- Open call4me in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Other MCP clients
Add this to your client's mcpServers config.
{
"mcpServers": {
"call4me": {
"type": "http",
"url": "https://call4.me/mcp"
}
}
}README
call4me
Your coding agent (Claude Code, Codex, Claude Desktop, ChatGPT) gets one new tool: make a phone call. Prepaid credits from $10 via Stripe Checkout, reloading monthly by default; one MCP URL with the key in it.
How a call works
src/server/voice/prompt.ts: what the caller is told. The product lives here: no opening disclosure, no recording notice, no end-of-call read-back; honest if sincerely asked whether it's an AI.src/server/voice/session.ts: the audio relay and back-office functions.src/server/services/dialer.ts: placing calls, per-account numbers, answering callbacks.src/server/mcp/server.ts: the MCP tools.
The app does not request recording when dialing or answering. Existing recordings stored by Telnyx
can be played or opened from the signed in call page after a call ends, or retrieved using call4me_get_recordings({ call_id }) over MCP, or
GET /api/calls/{call_id}/recordings with a call4me API key or OAuth token in the Bearer header.
Both check account ownership before contacting Telnyx and return fresh download links without
storing them. Empty results can mean processing is pending or no recording was saved. Links may
expire and should only be shared with the account owner.
Trunk recordings use call leg IDs. A separate provider ID table receives these from verified webhooks; existing calls resolve them from an exact control ID match in Telnyx webhook history. The app never guesses a match from phone numbers or timestamps. If provider history has expired and no mapping was saved, only recordings directly associated with the control ID can be found.
The recording lookup never contacts the voice session or changes prompts, live tools, audio, or Telnyx recording settings. Existing call status and transcript responses are unchanged.
The recording API's OpenAPI document is served at /api/openapi.json. Run
npm run openapi:generate to regenerate openapi.json from the shared MCP and HTTP schemas.
CI checks the generated artifact for drift. Run npm test, npm run check, npm run lint,
and npx wrangler deploy --dry-run before deploying through git.
Menu recovery tracks fresh phone prompts separately from transcript timestamps and remembers accepted keypad submissions. Repeated menus, invalid input, and recorded instruction dead ends can restart the existing back office after the recording goes quiet. It waits for pending tools and their continuations, avoids interrupting holds or a person answering, and asks the model to choose a supported route from the heard options rather than blindly replaying digits.
npm test includes provider message replay tests for recovery and its timing races. To evaluate
the configured back office model against synthetic menu scenarios, run npm run test:menu:live
with OPENAI_API_KEY (or a local .dev.vars). This opt-in evaluation calls OpenAI, inspects
the proposed tool calls, and never executes a tool or places a phone call.
Setup
- Telnyx: a Call Control application (its id is
TELNYX_CONNECTION_ID) with webhook URLhttps://<host>/webhooks/telnyx, an API key, and the account's webhook public key. Each account's number is bought on its first call and attached to that application. - OpenAI: an API key with GPT-Live access.
- Stripe: webhook endpoint
https://<host>/webhooks/stripeforcheckout.session.completed,checkout.session.async_payment_succeeded,invoice.paid,customer.subscription.updated,customer.subscription.deleted,charge.refunded. The blog's supporter subscriptions arrive on the same endpoint, taggedapp=callbay, kind=supporter(seesrc/server/services/supporters.ts).
Credits
Everything is prepaid. Loads start at $10 and, by default, the same amount reloads monthly (a Stripe
subscription; invoice.paid adds the credits). A call holds its maximum cost before it dials, in one
conditional insert so parallel calls can't overspend, and settles to the real talk time when it ends.
4. Secrets (wrangler secret put): see src/server/env.d.ts.
Two Workers
Call sessions run in their own Worker, call4me-voice (wrangler.voice.jsonc, src/server/voice/worker.ts),
which also takes Telnyx's media streams on voice.call4.me. Deploying a Worker resets the durable objects it
defines, so with the sessions split out the site deploys freely without dropping a call. CI deploys the voice
Worker with scripts/deploy-voice.sh, which skips an unchanged bundle and otherwise waits until no call is up,
deploys, and holds new calls until the new version is serving plus a minute for Cloudflare to retire the old
one. Never deploy it or change its secrets any other way: either restarts every live call. The voice Worker's secrets are
OPENAI_API_KEY, TELNYX_API_KEY, TELNYX_CONNECTION_ID, RAINDROP_WRITE_KEY and STREAM_SECRET (the same
value as the site's): npx wrangler secret put <NAME> -c wrangler.voice.jsonc.
Blog
/blog is markdown files in src/content/blog (one per post, listed in index.ts, headline image at
public/static/blog/<slug>.svg), with an Atom feed, likes, comments, an email newsletter (sent from
/admin/blog, for the ADMIN_EMAILS accounts), and paid posts for monthly supporters.
Self-hosting
Fork it, create your own D1 database (wrangler d1 create callbay) and put its id and your own hostname in wrangler.jsonc.
Local: npm run db:migrate:local && npm run dev with a .dev.vars holding the same secrets.
AI monitoring
Raindrop monitors the live conversation (callbay_voice_call), back office model runs
(callbay_back_office), and the recap after hangup (callbay_call_recap). Each event uses
the account ID as its user ID and the call ID as its conversation ID. Model names, timing,
status, and back office tool spans are included. No phone audio or recording URLs are uploaded.
Add RAINDROP_WRITE_KEY to .dev.vars locally and configure the same key as a Cloudflare
Worker secret with npx wrangler secret put RAINDROP_WRITE_KEY. Optional
RAINDROP_PROJECT_ID selects a project slug; unset uses the write key's default project.
Without a write key, monitoring is disabled. .dev.vars.example lists these optional settings.
AI inputs and outputs use Raindrop's PII redaction, with Callbay's existing masking for per call secrets applied first. Tool arguments and results appear in redacted back office AI output. Tool spans contain names, timing, and generic failure status, keeping sensitive payloads out of unredacted trace attributes. Account names and emails are not sent as user traits. SDK PII redaction is pattern based and does not guarantee removal of every sensitive detail.
Monitoring runs separately from live audio and tools. Terminal events and queued tool spans are flushed within the Worker or Durable Object lifetime. An unfinished back office run at hangup is marked interrupted; later tool results do not reopen the closed monitoring client.
After a call, check the three event names in Raindrop, with actual inputs and outputs, the matching account and call IDs, and tool names and durations. A call that never invokes a back office model has no back office event. Feedback signals, audio attachments, and agent self diagnostics are not instrumented because the current call flow has no corresponding feedback controls or diagnostics tools.
For investigation, connect the Raindrop MCP server and install
the investigation skill with npx skills add raindrop-ai/skills --skill raindrop-investigate.
Connect Slack in Raindrop for alerts. Create a Raindrop account if needed.
License
MIT
Source: README.md at commit 46735a4
Tools
0Version history
1- v1.0.0LatestOct 1, 2026
