Vexa
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Descripción del creador (original en inglés)
Deterministic pre-send lint for SMS/iMessage: silent carrier filtering and segment blowups.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
AGENTPHONE_API_KEYLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"willitsend": {
"command": "npx",
"args": [
"-y",
"willitsend"
],
"env": {
"AGENTPHONE_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add willitsend --env AGENTPHONE_API_KEY=your-value -- npx -y willitsendCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"willitsend": {
"command": "npx",
"args": [
"-y",
"willitsend"
],
"env": {
"AGENTPHONE_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"willitsend": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"willitsend"
],
"env": {
"AGENTPHONE_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub abryfs, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: AGENTPHONE_API_KEY
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.1.0) llegó al registro hace 4 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Vexa, emailmd, MCP WhatsApp Cloud
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.
Render markdown into email-safe HTML, lint drafts for deliverability problems, and preview emails.
MCP server for WhatsApp Cloud API (Meta) — messages, media, and templates via Graph API
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Your AI agent sends texts. Carriers silently drop the non-compliant ones, and the API never tells you. willitsend is the missing check between the model and the carrier: a deterministic preflight for outbound SMS/iMessage that catches silent filtering, segment blowups, and dropped iMessage features before you spend the send.
[Try it in the browser](https://abryfs.github.io/willitsend/): runs client-side, nothing leaves the page.
npx -y -p github:abryfs/willitsend willitsend-cli "Hey! Your appointment is tomorrow at 2pm." --first-message
Verdict: BLOCK
Segments: 1 (gsm7, 41 septets) Channel: unknown [BLOCK] first-message.opt-out: First message doesn't include opt-out instructions (e.g. "Reply STOP to unsubscribe"). Carriers may silently filter first messages that lack one, with no API error. Fix: Append "Reply STOP to unsubscribe." to the message body. Source: https://docs.agentphone.ai/documentation/reference/messaging-rate-limits#first-message-requirements [WARN] first-message.opt-in: No opt-in acknowledgment language found … [INFO] first-message.brand: No brand_name was provided …
Messaging APIs report "sent" when a message reaches the downstream carrier, not when it reaches a phone. AgentPhone's rate-limit docs spell out the consequence: first messages that skip brand identification, opt-in acknowledgment, or opt-out instructions "may be silently filtered by carriers. The API will not return an error."
AI agents now send texts autonomously, and nothing sits between the model and the carrier. An agent that drops the opt-out line gets no error and no delivery. An agent that adds one emoji turns a 160-character message into three billable segments and never notices.
willitsend is the missing check: a deterministic, stateless lint for a draft message. Text and context in, verdict and evidence out. It sends nothing and stores nothing.
sequenceDiagram
participant A as AI agent participant W as willitsend participant API as Messaging API participant C as Carrier participant P as Phone
rect rgba(255,69,58,0.08) note over A,P: without preflight A->>API: send_message (no opt-out language) API-->>A: "sent" ✓ C--xP: silently filtered. no error, no delivery end
rect rgba(52,199,89,0.08) note over A,P: with preflight A->>W: preflight_message(draft, context) W-->>A: BLOCK · missing opt-out · fix + citation A->>W: preflight_message(fixed draft) W-->>A: PASS A->>API: send_message API-->>A: "sent" ✓ C->>P: delivered end
A fair question: AgentPhone's docs are agent-readable, so you could feed them into every generation call and ask the model to comply. Two things break, and one gets expensive:
| Approach | Tokens per message | 10,000 msgs/day at $3/M input |
|---|---|---|
| Feed both AgentPhone doc pages into each generation call | ~7,700 | ~$231/day (~$23/day with 90% prompt caching) |
preflight_message call result (default) | ~250 (+ ~1,450 once per session for the tool definition) | ~$7.50/day |
preflight_message with response_format: "concise" | ~4 on pass, ~44 on block (measured) | ~$0.35/day at a 90% pass rate |
Roughly 30× fewer tokens per message in default mode — several hundred× in concise mode — and the checker's own compute rounds to zero (~4µs locally, no API). If you compress the rules into your system prompt instead — our skill file does, at ~950 tokens — you keep the compose-time benefit but still have no verifier and no segment math. Bulk senders feel this most: the tool exists precisely for AI agents sending texts at volume.
As an MCP tool (Claude Code):
claude mcp add willitsend -- npx -y -p github:abryfs/willitsend willitsend-mcp
or in any MCP client config:
{
"mcpServers": { "willitsend": { "command": "npx", "args": ["-y", "-p", "github:abryfs/willitsend", "willitsend-mcp"] } } }
For AI agents — paste this block into your agent (or point it at this README):
Install the willitsend MCP server (pre-send SMS/iMessage lint, no API key needed):
claude mcp add willitsend -- npx -y -p github:abryfs/willitsend willitsend-mcpThen, before every send_message (or equivalent) call, call preflight_message with the draft body, is_first_message_to_contact (true/false when known), and brand_name. Treat verdict "block" as do-not-send: apply the returned fix strings and re-run until pass. Treat "needs_context" as a signal to determine whether this is a first message (check conversation history), never as permission to send. For high-volume loops pass response_format: "concise" (~4 tokens on pass).
No API key required. Set AGENTPHONE_API_KEY if you want a live iMessage/SMS capabilities lookup for phone-number destinations; without it the tool runs offline. The config above installs straight from this repo (a prepare script builds on install) — nothing to sign up for. willitsend also publishes to npm and the MCP Registry under the server name io.github.abryfs/willitsend; once a release is cut, registry-aware clients can add it by name and npx -y willitsend starts the server directly. See docs/publishing.md for the release runbook.
As a library (npm install github:abryfs/willitsend):
import { preflight } from "willitsend";
const report = preflight({ body: "Acme: thanks for signing up. Your order shipped. Reply STOP to unsubscribe.", is_first_message_to_contact: true, brand_name: "Acme", });
report.verdict; // "pass" | "warn" | "block" | "needs_context" report.findings; // each with severity, fix, and a citation URL report.trace.segments; // { encoding, units, segments, perSegment, ... }
As a CLI: npx -y -p github:abryfs/willitsend willitsend-cli --help (or npx -y -p willitsend willitsend-cli once installed from npm). Exit codes: 0 pass/warn, 1 block, 2 needs context, 3 usage error. It drops into CI or a shell pipeline as-is.
| Rule | Severity | Source |
|---|---|---|
first-message.opt-out: first message to a contact must carry opt-out instructions | block | AgentPhone docs |
first-message.brand: first message must identify the brand (checked only against a brand_name you provide, never guessed) | block | AgentPhone docs |
first-message.opt-in: first message should acknowledge how the contact opted in | warn | AgentPhone docs |
first-message.media-only: compliance text can't ride in an image | warn | AgentPhone docs |
segments.unicode-blowup: one non-GSM character re-encodes the whole message as UCS-2 | warn | AgentPhone docs |
imessage.feature-fallback: send_style, threaded replies, and carousels drop without a trace on SMS fallback | warn | AgentPhone docs |
imessage.invalid-send-style, imessage.carousel-count: invalid effect names, carousels outside the documented 2-20 range | block | AgentPhone docs |
imessage.new-contact-cap: iMessage caps new-contact sends at 50/day per line | info | AgentPhone docs |
destination.invalid, destination.voip: malformed destinations; known-VoIP lines (line type is never guessed from the number) | block / warn | send API / AgentPhone docs |
content.shaft: sex/alcohol/firearms/tobacco terms carriers filter (hate speech has no keyword rule: word lists can't detect it and we don't pretend) | warn | Twilio guidelines |
content.url-shortener: shared public shorteners (bit.ly, tinyurl, …) conflict with CTIA dedicated-shortener guidance | warn | CTIA MP&BP (PDF) |
content.spam-patterns: ALL-CAPS runs, $$$, !!! | info | heuristic |
Rules come in two labeled tiers. Rules sourced from AgentPhone's own documentation can block. Industry-sourced rules warn at most, because a keyword heuristic has no business vetoing your send.
A finding that depends on context you didn't supply doesn't pretend to be certain. If you never say whether this is the first message to a contact, the opt-out rule reports conditionally and the verdict is needs_context. You get no fake pass and no fake block.
flowchart LR
F[findings] --> B{any block finding with known context?} B -- yes --> BLOCK B -- no --> C{any block finding waiting on context?} C -- yes --> NC[NEEDS_CONTEXT] C -- no --> W{any warning?} W -- yes --> WARN W -- no --> PASS
Every report also carries a send trace: destination classification, assumed channel (iMessage/SMS/MMS), full segment math (encoding, septet and code-unit counts, placement-aware per-segment packing), and, given a 10DLC campaign tier, what this message costs against published daily segment caps.
Reproduce every number here from the repo; none of them require an account.
test/parity.test.ts; run npm test.npm run bench on yours. Preflighting evSolo se muestra el principio; lee el resto en el repo