Build, deploy, and sell AI agents for local-service businesses - from your IDE.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
Manual Client & Custom JSON ConfigExpand JSON ▾
Client Config & Setup
Choose your client or environment
Target File:
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Documentation Overview
SeldonFrame
Sell AI front offices. Deploy them in minutes.
SeldonFrame is the agent-native, open-source alternative to GoHighLevel for agencies serving local businesses. Give your coding agent a client's URL and it can create a branded website, booking flow, intake, CRM, and AI agent in one workspace. Run evals, publish, and hand it off — then operate every client from one agency view.
Website · For agencies · For builders · Docs · Discord
Live demos: HVAC · Med spa · Med spa · Weight loss
Ship your first client front office
Or as an auto-updating Claude Code plugin:
Build the first client workspace before paying. Hosted Managed uses SeldonFrame's keys; Builder and Agency plans are BYOK. Your agency owns the client relationship, workspace data, and delivery margin.
See a real one — a live workspace, not a mockup:
|
|
| The generated site — quote intake, reviews, and the chat agent (bottom right) | Its booking page — the real calendar the agent books against |
And here's the agent on that site handling a real inbound — checking the live calendar, and, when asked for a price, refusing to invent one (that's the quote-guard, not a scripted reply):
|
A genuine exchange with the chatbot on the live site — nothing scripted:
Same agent answers on SMS and voice too — the channel is just a config knob. |
Click any screenshot — this HVAC workspace is live and books real appointments. More live workspaces: Metro MedSpa · SKINNEY Medspa · Vive Ageless Weight Loss — and more on seldonframe.com.
The agency delivery loop
- Start with the client URL. SeldonFrame extracts the business facts and creates the workspace.
- Apply your agency playbook. Brand the site, booking flow, intake, CRM, and agent.
- Verify before handoff. Run evals and complete a real test booking.
- Publish and operate. Give the client a branded portal while your agency keeps the master view.
The same loop works from the dashboard, Claude Code, Cursor, Windsurf, or any MCP-compatible agent. See the agency workflow.
What an agent is made of here
Most "agent frameworks" hand you a chat loop and wish you luck. SeldonFrame gives your IDE agent the full production anatomy:
The agent model — Trigger × Skill × Channel
An agent isn't a chatbot UI; it's three independent axes:
- Trigger — when it runs: inbound (a call / chat / email / SMS arrives) · event (a domain event fires —
booking.completed,lead.created,invoice.paid…) · schedule (a cron cadence). - Skill — what it does: receptionist · review-requester · speed-to-lead · win-back · digest…
- Channel — how it speaks: voice · web chat · SMS · email · internal digest.
- Tools — what it can touch: native tools (book against the real calendar · read/write the CRM · send SMS & email · take a message) plus 1,000+ app integrations via Composio (Google Calendar, Sheets, Slack, HubSpot, Notion, …), bound per-agent.
surface: voice | chat (the old receptionist-only knob) is just one point in this space — trigger=inbound. One builder creates any agent; the marketplace sells any agent.
From agent to production loop
A production agent is a loop, not a single prompt:
Trigger → (Model + Tools + State) → Verify → Iterate, bounded by a Stop condition, improved by Evals, kept honest by Observability + Guardrails.
Two non-negotiables drive the roadmap: the checker must be separate from the maker (a model grading its own work is too generous a grader), and the loop must have brakes (or it bills you in silence). Where each primitive stands today:
| Primitive | Status | What's there |
|---|---|---|
| Trigger | ✅ Shipped | Inbound + event triggers on the SeldonEvent bus. booking.completed → review-requester; lead.created → speed-to-lead, both sending outbound SMS/email. |
| State | ✅ Shipped | Agent loop-memory in Brain v2 — agents recall what they did before acting and record after. The review "ask once per customer" throttle is now a memory recall, not a bespoke flag. |
| Verify (maker ≠ checker) | ✅ Shipped | Deterministic validators grade every run — pass rates surface on each agent's health card and /runs; run_agent_evals replays scripted scenarios. Rolling out: the same checker as a hard pre-send gate + an LLM judge for judgment calls. |
| Guardrails / Stop | ✅ Shipped | Quote-guard (never invent prices), enforced read-back before booking, per-contact throttles, booking-policy enforcement (hours · duration · required fields), hard call/iteration caps. Rolling out: generic token-budget brakes for long-looping agents. |
| Generate-by-default | ✅ Shipped | One English sentence → trigger + skill + channel + tool bindings + guardrails, generated together. "text every customer for a Google review the day after their job — never twice, only if completed" compiles into a real agent. The generate_agent MCP tool and the Studio wizard both run this pipeline. |
| Record → Agent | 🗺 Roadmap | Skip describing it — screen-share your workflow once. SeldonFrame watches, compiles the steps into a draft agent (skill + tool bindings + eval scenarios derived from the recording), and you deploy in minutes. Live behind a flag at /record; becoming the default on-ramp next. |
The loop, drawn
One sentence builds it; triggers drive it; the ring is the loop running — Model → Tools → State → Verify — with tools orbiting the core,
/runs+ Brain observing, and the Stop brakes bounding every pass. Everything in the diagram is shipped today. (Animated SVG — if your viewer freezes it, the still frame reads the same.)
Deeper — the pre-wired stack, the architectural bet, the roadmap: docs/ARCHITECTURE.md.
Five agents you can ship today
Trigger × Skill × Channel are independent axes — pick one of each and you've architected an agent:
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