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Hail.so – Send and receive emails, calls, SMS via a single MCP/API/CLI

Hacker News

Hail.so – Send and receive emails, calls, SMS via a single MCP/API/CLI

Hello HN, Hail is an MCP server, CLI and API for email, SMS and phone calls. Inbound and outbound. It packages Twilio, AWS SES (with or without custom domains), LiveKit, ElevenLabs, Cartesia, and LLM providers under a consistent API. The implementation comes from about a year of production work building industrial AI voicebots, and tooling for all sorts of AI agents. Check the README for the current stack and milestones for what's coming. Open source, self-hostable backend: https://github.com/hail-hq/hail/ How this project came about? ---------------------------- I spent over a year as CTO of an AI startup building a useful chatbot + voicebot for industrial companies, and the most useful features turned out to be: > generating documents and sending them via emails > calling staff members to collect specific information like "where did you leave the key to the building" or "what's the specific values to set for the oil refining machine" > sending SMS reminders for staff to do XYZ However it was pretty hard to get all 3 working well, and at a low cost: sending and receiving emails, phone calls, and sms. It requires several days at best to connect Twilio SIP trunks to a server to handle them, then set up AWS SES to send emails, etc. and that is if you know what you're doing, and not starting from scratch. Plus, each provider would give you a separate invoice you'd have to do bookkeeping for. So I've put all the learnings to work in a single project, not only so that I don't loose the learning, but also because every company needs to give their AI agent or backend a way to communicate with the world via email, phone, or SMS. A single API, MCP, and CLI. Why not just set up my own Twilio + Resend + Postmark? ------------------------------------------------------ > separate integrations for email, voice and SMS. Takes very long to set up > deploying telephony requires SIP infrastructure > several dashboards, messy UI/UX > several bills to keep track off in bookkeeping > no native MCP server or CLI for AI agents This project is not replacing existing providers (twilio, amazon ses, etc), but packages them into a single platform with sane defaults. Where are we at? ---------------- Right now Hail has good support for outbound phone calls and emails, and the inbound emails is well underway for a final release using auto-forwarding and webhooks. What is left is support for inbound phone calls, and SMS inbound/outbound. What next? ---------- You can host the project yourself or check out https://hail.so/

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agents, agent · Missing: macos, cursor, claude
94%94% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way, para · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus, platform, host · Missing: intuitive, reviews, exclusive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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