
SignalPipe
io.github.AbYousef739由 GitHub 账号 AbYousef739 发布v2.1.3更新于 Oct 24, 2026
Buying-intent judgement for AI agents: a three-judge panel scores any text as buyer or not.
概览
SignalPipe 将文本判定为购买意向,把合格线索连同草拟回复加入队列,并跟踪潜在客户的培育进度。
- 可以做什么
- SignalPipe 判断帖子、邮件或工单的作者是否有购买意向,对边界情况使用三名评审组成的小组进行裁决。它列出待处理线索及其评分和草稿,允许助手批准、拒绝或删除任务,并可上传由宿主模型撰写的草稿。培育引擎跨 14 种信号类型跟踪潜在客户的温度并生成下一条外联消息,可选的 Reddit 发送器使用用户自己的凭据发布已批准的评论和私信。
- 适用场景
- 当助手需要监控信息源或粘贴的文本以发现购买信号,并管理带有草拟回复的销售线索队列时使用。它适合从事社交销售或线索资格评估的团队,希望在一个工作流中完成评分、起草和潜在客户培育。
- 运行要求
- 远程 MCP 端点 Authorization Bearer 操作员密钥。托管的评分和起草后端需要付费订阅。可选的 Reddit 发送需要 REDDIT_CLIENT_ID、REDDIT_CLIENT_SECRET、REDDIT_USERNAME 和 REDDIT_PASSWORD 环境变量。
安装
在 SourceWeft 中
- 打开 控制台中的 SignalPipe,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
交给智能体安装
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/io.github.AbYousef739%2Fsignalpipe/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。其他 MCP 客户端
把它添加到你客户端的 mcpServers 配置中。
{
"mcpServers": {
"signalpipe": {
"type": "http",
"url": "https://api.signalpipe.io/mcp"
}
}
}README
SignalPipe
Agentic sales pipeline — buying-intent detection, swarm-scored lead qualification, and prospect nurturing for OpenClaw agents.
SignalPipe judges whether the author of a post, email or ticket wants to buy. Your agent brings the text from anywhere it reads, including X through your own X API access, and an optional scout reads the RSS or Atom feeds you choose. Three independent judges rule on every borderline signal, each kept lead gets a drafted reply that answers what the person actually asked, and only real leads reach you for approval. Works with any OpenClaw-compatible agent — or connect directly via MCP from Claude Code, Cursor, or Windsurf.
signalpipe.io · Smithery · Glama
What It Does
Top of funnel — Signal Acquisition (Mantidae): Your agent brings text from anywhere it reads, and the optional scout reads the RSS or Atom feeds you choose every cycle. Clear-cut posts are decided on content alone; borderline ones go to three independent judges (Skeptic, Analyst, Optimist), and when they split you see it. Only real leads reach your queue, each with a drafted reply that answers what the person asked and mentions your product only when they asked for a tool.
Competitor-switch posts are hard-floored and always reach your queue regardless of score.
Mid/bottom of funnel — Nurture Engine: Tracks every prospect's temperature (0–100) across 14 signal types. Automatically selects the right persona (Educator → Consultant → Closer → Re-engager). Remembers objections permanently — if someone said the price is too high, that angle is never repeated. Never spams. One-directional mode transitions.
Execution — Sender (v2.0):
The brain scores, drafts, and approves; the plugin can now also send. An optional background sender holds a live stream open to the brain, receives the missions you've already approved, and posts reddit_comment / reddit_dm on Reddit with your own credentials. The math runs on us, the sending runs on you — your Reddit credentials and LLM keys never reach SignalPipe. twitter_reply is handled by the standalone signalpipe-daemon. The sender is opt-in: set the REDDIT_* env vars to enable it, or ignore it entirely and stay MCP-only. Private messages go only to someone who asked for one: Reddit and X both require the recipient's consent before an app sends one. SignalPipe never auto-sends a DM or an X reply; each waits for your approval.
Tools (29 total)
Signal Acquisition
Nurture Engine
Sender
Reddit-only; requires the optional REDDIT_* env vars. Contains no scoring or drafting — it only posts pre-approved missions with your credentials.
Reader
Reads feeds from this machine. No credentials and no extra dependencies.
MCP Support
SignalPipe exposes all tools as an MCP server — no OpenClaw plugin install needed.
Connect from Claude Code, Cursor, or Windsurf — add this URL to your MCP config:
Auth: Authorization: Bearer YOUR_OPERATOR_KEY
Once connected, ask your agent:
- "Show me my leads"
- "Reject the first one — it's a founder promoting their own tool"
- "Who should I follow up with today?"
Live Session Example
A typical morning lead review inside your OpenClaw agent or Claude.ai via MCP.
You: Show me today's leads.
Agent: 2 leads ready. Lead 1 is a competitor-switch signal, score 91 — Closer draft, proposes a direct next step. Lead 2 is a genuine need with flexible budget, score 68 — Advisor draft, leads with their real problem. Lead 3 was auto-rejected by the swarm. Approve 1 and 2, or edit first?
You: Lead 1 is good, approve it. For lead 2 change the draft to: "Hey Rachel — we solve exactly this. Most ops teams are running automations within a day. Want me to show you how a team like yours uses it?"
You: Rachel just replied — she's interested. Log it.
Agent: Rachel is in Sales mode, temperature 45. Consultant persona active — qualify and show fit, no hard sell yet.
You: Who's hottest? Generate a message for them.
Agent: Closing mode, friction-removal tactic. Her previous pricing objection is permanently on record — the AI avoided that angle automatically.
Quick Start
1. Get a backend + operator key
Subscribe at signalpipe.io, sign in to the console with the email you paid with, and create your SIGNALPIPE_OPERATOR_KEY there (it is shown once). The backend URL is https://api.signalpipe.io. No infrastructure to manage.
2. Install
Via OpenClaw:
Via MCP (no plugin install): Add the MCP server URL to Claude.ai, Cursor, or Windsurf — see MCP Support above.
3. Set environment variables
Optional — to run the in-plugin Reddit sender (v2.0): add a Reddit "script" app's credentials (create one at https://www.reddit.com/prefs/apps on the sending account; since November 2025 Reddit reviews new API apps under its Responsible Builder Policy before issuing them). These stay on your machine and are never sent to SignalPipe.
4. Configure a product
Ask your agent:
"Set up my product. It's called AcmeTool, it automates repetitive ops workflows, and it's bought by ops leads and founders."
The agent drafts buyer-voice anchors with signalpipe_suggest_anchors (for example "we're drowning in the same manual handoffs every week"), shows them to you to edit, then adds the product. Before adding a feed, have it run signalpipe_preview_station on the feed: it says whether buyers actually post there.
The signal engine activates on the next scout cycle.
How Scoring Works
Every incoming post passes through two sequential pipelines.
Pipeline 1 — Scoring (backend):
- Optional keyword gate — only if you set
buy_signal_keywords. A post matching none of them is dropped before anything reads it, so leave the list empty unless your buyers use a fixed vocabulary. - Multi-factor semantic scoring — embedding similarity, urgency, specificity, and keyword density. Multilingual: English, Spanish, French, German, Portuguese, Finnish.
- Sarcasm detection — distinguishes genuine buyers from venting or irony. Fails open — real leads are never suppressed by the sarcasm check.
Pipeline 2 — Swarm Drafting (managed backend):
Posts that survive scoring reach a 3-judge AI swarm:
The judges run concurrently, and their scores are fused via a weighted ensemble. Low-confidence leads are auto-rejected — they never reach your queue. When the judges keep a lead, a separate writer drafts the reply: one concrete answer to what the person asked, in two or three sentences, mentioning your product only when they asked for a tool. If the writer is unavailable, the judges' own draft is used instead, pitched to how strong the signal is:
- Closer (highest-intent): Proposes a concrete next step — demo link, trial, or direct ask
- Advisor (mid-intent): Consultative — acknowledges situation, introduces product naturally
- Educator (early-stage): Value-first — answers their question, mentions product only if it fits
Reinforcement learning: Every approve/reject adjusts the source station's RL weight — each listening feed (subreddit, HN search, RSS source) carries its own multiplier. Approvals reward the feed; rejections are reason-aware, with the penalty sized to how bad the signal was — spam is penalised hardest, then wrong-audience, then weak or no-reason rejections, while sarcasm and wrong-product are lighter and "already a customer" carries no penalty. Per-station scoping means one noisy feed gets demoted without penalising the rest of the product's sources.
Temperature Model
Mode is intent-based, not pure temperature. Brand-new prospects start in
nurture regardless of their starting temperature and only move out once a
real signal lands.
14 signal types map to calibrated heat deltas: booked_demo, asked_pricing, viewed_content, replied, clicked_link, not_decision_maker, ghosted_3_days, no_time, competitor, too_expensive, not_interested, bad_timing, ghosted_7_days, opted_out. With the reply text in hand, signalpipe_record_reply reads it and sets the signal for you.
One-directional mode transitions — no oscillation, no spam. Objection memory — permanently recorded and injected into every future message so the AI never repeats a failed angle.
Pricing
The plugin and the daemon are free and MIT licensed. The managed brain — scoring and drafting — is a subscription, metered in judgements (one three-judge panel run). Text that is clearly noise or clearly a buyer is decided without convening the panel and spends nothing.
Billed monthly through Stripe; cancel any time from your billing page. Every scoring call returns how much of the month is left. Current details: signalpipe.io/pricing.
Reading your feeds on this machine
Some stations can be read from your own machine instead of by the brain: they show read_by: "client" in /stations/list. signalpipe_read_feeds fetches those feeds from here, at most 50 posts per feed and a minute between feeds (Reddit limits how fast one machine may read), and hands each page to the brain, which scores the posts as if its own scout had read them. Run it once, or with every_minutes to keep reading. The standalone signalpipe-daemon does the same with signalpipe-daemon read.
Checking a feed before you add it
signalpipe_preview_station reads a candidate feed on this machine and has the brain judge its best-matching posts, without saving anything. The verdict comes from thresholds fixed in advance: VIABLE (real buyers post here), MARGINAL (a trickle), ON-TOPIC, NOT IN-MARKET (people discuss your topic but nobody is asking to buy, usually makers or support questions), NO BUYERS, or NO DATA (nothing could be judged; the explanation says why, such as an empty or stale feed or keywords that blocked every post). Each judged post costs one judgement. Which communities you listen to decides results more than any setting, so check before you add.
Sending from your own accounts
The drafts are written by AI. Reddit asks that AI-generated content be disclosed, and both Reddit and X act against automated posting, so read and edit each draft in your own words before it goes out. Public Reddit comments, X replies and DMs are never sent without a person approving each one.
The in-plugin sender posts approved missions with a Reddit script app on your account. Since 11 November 2025 Reddit issues new API apps only after a manual approval, so if you do not already have one, skip the sender: approve drafts in your agent, post them yourself, and the queue works the same. X sending lives in signalpipe-daemon and needs a paid (pay-per-use) X API account.
License
Plugin: MIT. The managed brain is a hosted service and is not distributed.
来源:README.md,提交 39128ea
工具
0版本历史
5- v2.1.3最新Sep 29, 2026
- v2.1.2Sep 29, 2026
- v2.0.5Sep 25, 2026
- v2.0.4Sep 24, 2026
- v1.5.0Sep 16, 2026
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