原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Willitsend

作者:abryfs版本 0.1.0i★ –i在你的电脑上运行
注册名称io.github.abryfs/willitsend

安装

概览

作者提供的说明(英文原文)

Deterministic pre-send lint for SMS/iMessage: silent carrier filtering and segment blowups.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 聊天与邮件
  • 你需要填写:AGENTPHONE_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: AGENTPHONE_API_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "willitsend": {
      "command": "npx",
      "args": [
        "-y",
        "willitsend"
      ],
      "env": {
        "AGENTPHONE_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add willitsend --env AGENTPHONE_API_KEY=your-value -- npx -y willitsend

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "willitsend": {
      "command": "npx",
      "args": [
        "-y",
        "willitsend"
      ],
      "env": {
        "AGENTPHONE_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "willitsend": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "willitsend"
      ],
      "env": {
        "AGENTPHONE_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • AGENTPHONE_API_KEY 机密 env
    Optional API key for live carrier/capabilities lookup. The linter runs fully offline without it.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 abryfs 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“聊天与邮件”中的其他服务器比较i

  • 星标数多于此分类中其他 1766 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1766 个服务器的 17% 更新
  • 基础检查结果等于或优于此分类中其他 1766 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Willitsend 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:AGENTPHONE_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.0)于4个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Vexa, emailmd, MCP WhatsApp Cloud

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Vexa

作者:Vexa-ai

Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.

在云端运行★ 2,949Apache-2.02个月前更新
安装

emailmd

作者:anypost

Render markdown into email-safe HTML, lint drafts for deliverability problems, and preview emails.

电脑或云端★ 1,385MIT31天前更新
安装

MCP WhatsApp Cloud

作者:codespar

MCP server for WhatsApp Cloud API (Meta) — messages, media, and templates via Graph API

在你的电脑上运行★ 277MIT5个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

willitsend

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 …

The problem

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

Why not just prompt the rules into your agent?

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:

  1. Generation is probabilistic; verification is deterministic. A model with the rules in context complies *usually*. This checker returns the same verdict every time, and its failure mode is a visible finding rather than a silently filtered message. Compose-time guidance and pre-send verification are complements — this repo ships both (the agent skill is the compose-time half).
  2. Models can't do segment math. Septet counting, GSM-7 extension characters, encoding flips from one smart quote, placement-aware packing — token-based models are structurally bad at exactly this arithmetic. No amount of prompting fixes it; a 300-line deterministic function does.
  3. The token math, measured (char-count/4 heuristic on the actual pages, July 2026):
ApproachTokens per message10,000 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.

Quickstart

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 Code: run claude mcp add willitsend -- npx -y -p github:abryfs/willitsend willitsend-mcp
  • Any other MCP client: add {"command": "npx", "args": ["-y", "-p", "github:abryfs/willitsend", "willitsend-mcp"]} to its MCP server config.

Then, 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.

What it checks

RuleSeveritySource
first-message.opt-out: first message to a contact must carry opt-out instructionsblockAgentPhone docs
first-message.brand: first message must identify the brand (checked only against a brand_name you provide, never guessed)blockAgentPhone docs
first-message.opt-in: first message should acknowledge how the contact opted inwarnAgentPhone docs
first-message.media-only: compliance text can't ride in an imagewarnAgentPhone docs
segments.unicode-blowup: one non-GSM character re-encodes the whole message as UCS-2warnAgentPhone docs
imessage.feature-fallback: send_style, threaded replies, and carousels drop without a trace on SMS fallbackwarnAgentPhone docs
imessage.invalid-send-style, imessage.carousel-count: invalid effect names, carousels outside the documented 2-20 rangeblockAgentPhone docs
imessage.new-contact-cap: iMessage caps new-contact sends at 50/day per lineinfoAgentPhone docs
destination.invalid, destination.voip: malformed destinations; known-VoIP lines (line type is never guessed from the number)block / warnsend 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)warnTwilio guidelines
content.url-shortener: shared public shorteners (bit.ly, tinyurl, …) conflict with CTIA dedicated-shortener guidancewarnCTIA MP&BP (PDF)
content.spam-patterns: ALL-CAPS runs, $$$, !!!infoheuristic

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.

The verdict model

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.

Benchmarks

Reproduce every number here from the repo; none of them require an account.

  • Segment-math parity: agrees with Twilio's reference segment calculator on encoding and segment count across a frozen 126-vector corpus: GSM-7/UCS-2 boundaries, extension characters, emoji, ZWJ sequences, and a deterministic fuzz sweep. The corpus and suite live in test/parity.test.ts; run npm test.
  • Latency: median ~4µs per message, ~100,000 messages/second on one thread (Node 22, Apple Silicon laptop; single-pass code-point tables, zero per-character allocation). Run npm run bench on yours. Preflighting ev

只显示了开头部分;其余内容请在仓库中阅读

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