SignalPipe
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SignalPipeShow me this week's hot leads"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SignalPipe
Agentic sales pipeline — buying-intent detection, swarm-scored lead qualification, and prospect nurturing for OpenClaw agents.
SignalPipe watches Reddit, Hacker News, X/Twitter, and any RSS feed you configure for people publicly expressing buying intent. A 3-judge AI swarm evaluates every signal, calibrates the reply to the signal strength, and surfaces only real leads for your approval. Works with any OpenClaw-compatible agent — or connect directly via MCP from Claude Code, Cursor, or Windsurf.
What It Does
Top of funnel — Signal Acquisition (Mantidae): Scouts Reddit, Hacker News, X/Twitter, and custom RSS feeds every cycle. Every post passes through a 3-stage scoring filter — keyword gate, multi-factor semantic scoring, sarcasm detection — then reaches a 3-judge AI drafting swarm: Skeptic, Analyst, Optimist. Each judge scores the lead independently. The swarm fuses their scores and suppresses low-intent posts automatically. Only leads that clear the swarm reach your queue — with a draft already calibrated to how hot the signal is:
Score > 80 (Closer): Direct, action-oriented reply — proposes a concrete next step
Score 61–80 (Advisor): Consultative — acknowledges the problem, introduces the product naturally
Score 40–60 (Educator): Value-first — leads with a genuine insight, mentions the product only if it fits
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 13 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.
Tools (17 total)
Signal Acquisition
Tool | What it does |
| List pending leads awaiting review — score, role, channel, snippet, draft. Lean by default; opt into |
| Get the drafting payload for a single mission so the host LLM can write the reply itself (BYOK path) |
| Upload a host-LLM-written draft to a mission |
| Approve a lead and queue it for outreach |
| Reject a lead with a reason — teaches the per-station RL loop (penalty size adapts to the reason; demotes one noisy feed without dragging the rest of the product down). Don't use this when the post is just gone — use |
| Hard-delete a mission row — silent cleanup, no learning signal. Companion to reject. Canonical case: the post was deleted / 404'd / removed before you could reply. |
| Trigger an on-demand scouting run across all active products |
| List all configured products |
| Register a new product to monitor — describe it in buyer language |
| Add an RSS feed, subreddit, or HN keyword feed for a product |
| Hot-reload product cache after changes — no redeploy needed |
Nurture Engine
Tool | What it does |
| Log a signal from a prospect, update their temperature |
| Generate the next outreach message via the backend LLM |
| Get the full prompt + context so the host LLM writes the message (BYOK path) |
| Record a host-LLM-written message as sent |
| View the full prospect pipeline sorted by temperature |
| Universal scorer — paste any text (Gmail, Slack, Discord, Telegram, LinkedIn, transcripts) and get back the same score + classification + drafting context the scout produces for Reddit/HN posts. SignalPipe never touches the source channel; your host agent does. |
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:
https://api.signalpipe.io/mcpAuth: 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.
→ signalpipe_get_missions3 missions pending review
MISSION 1 · score: 91 · role: CLOSER · competitor_flag: true
Product : AcmeTool
Channel : reddit_dm
Handle : u/frustrated_dev99
Snippet : "Their pricing just doubled again. Done. Need a replacement ASAP."
Draft : "Saw your post — we built AcmeTool for exactly the gap you're
describing. Teams typically switch in under a week. Worth a
quick look? Happy to show you how it compares."
MISSION 2 · score: 68 · role: ADVISOR · competitor_flag: false
Product : AcmeTool
Channel : reddit_dm
Handle : u/ops_lead_rachel
Snippet : "Looking for a tool to automate repetitive ops workflows.
Budget is flexible, need something the team actually uses."
Draft : "The part about 'something the team actually uses' is the real
problem to solve — most tools fail there, not on features.
AcmeTool is built around that constraint. Happy to walk through
a real team setup if useful."
MISSION 3 · score: 24 · role: EDUCATOR · competitor_flag: false
Product : AcmeTool
Channel : reddit_dm
Handle : u/just_browsing_thx
Snippet : "Saw an ad for workflow tools. Not really something I need right now"
Draft : [Swarm low-confidence — auto-rejected]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?"
→ signalpipe_approve_mission (msn_8f3a — swarm draft unchanged)
→ signalpipe_approve_mission (msn_2b91 — user-edited draft)✓ msn_8f3a queued for outreach
✓ msn_2b91 queued for outreach (your version)You: Rachel just replied — she's interested. Log it.
→ signalpipe_track_prospect
handle : u/ops_lead_rachel
channel : reddit_dm
signal : replied
mission_id: msn_2b91{
"prospect_id": "pro_7f2c",
"handle": "u/ops_lead_rachel",
"temperature": 45,
"mode": "sales",
"persona": "Consultant",
"follow_up_in": "2–3 days"
}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.
→ signalpipe_get_pipeline
→ signalpipe_get_message (prospect_id: pro_sarah_cto){
"message": "Sarah — you've seen how it works. Happy to answer any last
questions before your team makes a call. What's the main
thing you're still weighing?",
"tactic": "remove_friction",
"mode": "closing",
"temperature": 88,
"note": "Previous objection (too_expensive) on record — pricing angle avoided"
}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
Managed (recommended): Join the waitlist at signalpipe.io — you get a SIGNALPIPE_OPERATOR_KEY and backend URL. No infrastructure to manage.
Self-hosted: See Self-Hosting below.
2. Install
Via OpenClaw:
claw install signalpipeVia MCP (no plugin install): Add the MCP server URL to Claude.ai, Cursor, or Windsurf — see MCP Support above.
3. Set environment variables
export SIGNALPIPE_API_URL=https://api.signalpipe.io
export SIGNALPIPE_OPERATOR_KEY=your-operator-key4. Configure a product
Ask your agent:
"Add my product — it's called AcmeTool, it helps ops teams automate repetitive workflows, target audience is ops leads and founders, anchor phrases: 'automate repetitive tasks', 'workflow automation', 'ops without headcount'"
The signal engine activates on the next scout cycle.
How Scoring Works
Every incoming post passes through two sequential pipelines.
Pipeline 1 — Scoring (backend):
Keyword gate — pre-filter: any
buy_signal_keywordsmust appear before the post is scored. Eliminates ~85% of posts with zero API cost.Multi-factor semantic scoring — embedding similarity, urgency, specificity, and keyword density. Multilingual: English, Spanish, French, German, Portuguese.
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:
Judge | Role | Weight |
Skeptic | Vetoes non-buyers, sellers promoting their own tools, surveys | 40% |
Analyst | Assesses fit depth, writes the preferred draft | 35% |
Optimist | Finds the strongest read of the lead, fallback draft | 25% |
The judges run concurrently. Their scores are fused via ensemble weighting. Low-confidence leads are auto-rejected — they never reach your queue. High-confidence leads get a draft calibrated to signal strength:
Closer (>80): Proposes a concrete next step — demo link, trial, or direct ask
Advisor (61–80): Consultative — acknowledges situation, introduces product naturally
Educator (40–60): 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 are flat (+0.05); rejections are reason-aware (spam −0.04, not_relevant −0.03, no_reason / too_vague −0.02, sarcasm / wrong_product −0.01, already_customer 0.00). 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.
Mode | When | Persona |
Nurture | First-touch / no engagement yet (default for new prospects) | Educator — value-first, lead with insight, mention the product only if it fits |
Sales | Prospect engaged (replied / clicked / asked / viewed) and temperature 30–74 | Consultant — qualify, show fit, build trust |
Closing | Sustained engagement and temperature ≥ 75 | Closer — urgency, social proof, clear CTA |
Recovery | Previously engaged and cooled, or explicit cooling signal (ghosted_3_days, ghosted_7_days, not_interested, bad_timing) | Re-engager — re-spark cold leads, no hard sell |
13 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.
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.
Managed Backend Tiers
Tier | Price | Products | Leads/day | Prospects |
BYOK | $19/mo | 3 | 50 | 1,000 |
Starter | $49/mo | 2 | 25 | 500 |
Growth | $149/mo | 10 | 250 | 5,000 |
Scale | $499/mo | Unlimited | Unlimited | Unlimited |
Annual billing available — 2 months free (17% off). First 100 waitlist signups: 50% off for 3 months.
Self-Hosting
The backend is a FastAPI app. Requirements:
Python 3.11+
PostgreSQL with
pg_cronandpg_net(Supabase recommended)A host that supports long-running processes (Railway recommended)
OpenAI API key (embeddings)
Full setup guide: signalpipe.io/guide#self-hosting
License
Plugin: MIT
Backend: Business Source License 1.1 (converts to Apache 2.0 after 4 years)
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