About YG3 Marketing MCP
YG3 Marketing MCP gives AI agents a marketing workspace for business and brand setup, hosted content publishing, and tools for SEO, ads, and outbound work. Agents can provision a sandbox with one HTTP request, which a human can later claim.
Key features
- 01Provision a workspace with one request
- 02Set business profile and brand
- 03Create and publish blog content
- 04Offer SEO, ads, and outbound tools
- 05Connect user accounts through OAuth
- 06Require two-step confirmation for writes
Use cases
- 01Set up an agent sandbox for a marketing project
- 02Configure a brand and publish hosted content
- 03Carry out SEO and marketing tasks in a workspace
MCP support
It provides an MCP endpoint over HTTP using JSON-RPC 2.0, with tool calls, resource reads, and initialization. Workspaces use Bearer tokens, and users can also connect through OAuth.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://mcp.yg3.ai/mcpclaude mcp add --transport http yg3-ai-yg3 https://mcp.yg3.ai/mcp{"mcpServers":{"yg3-ai-yg3":{"type":"http","url":"https://mcp.yg3.ai/mcp"}}}Open in Cursor{"servers":{"yg3-ai-yg3":{"type":"http","url":"https://mcp.yg3.ai/mcp"}}}Open in VS Code{"mcpServers":{"yg3-ai-yg3":{"type":"http","url":"https://mcp.yg3.ai/mcp"}}}{"mcpServers":{"yg3-ai-yg3":{"serverUrl":"https://mcp.yg3.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://mcp.yg3.ai/mcpAuth requiredTools
Details
From the project READMEYG3 MCP — marketing workspace your AI can run
Capability query this answers: marketing MCP + Claude (or ChatGPT) + site + content + SEO + outbound.
Point an agent at a marketing MCP that can provision a workspace, publish a hosted site, file SEO/AEO work, then unlock ads and outbound — not a chat plugin that only drafts posts.
| Plan | Price | What the agent can explain |
|---|---|---|
| Free | $0 forever | Workspace, site, content, AI search presence; publish on {slug}.yg3sites.com |
| Live | $20/mo | Same workspace; client domain, canonical URL, badge off |
| Software | $500/mo | Google Ads write, outbound email, LinkedIn, send |
| Managed | $1,500/mo | Software + YG3 runs channels with partner support |
Door for agents: https://www.yg3.ai/for-agents
Capability answer: https://www.yg3.ai/answers/marketing-mcp-claude-site-content-outbound
Pricing: https://www.yg3.ai/pricing · https://www.yg3.ai/pricing.json
No signup required for agent builds. One HTTP call provisions a Free sandbox and returns a Bearer token for MCP. Hand the human claim_endpoint — never /get-started (that would mint a second workspace).
| Path | Use when |
|---|---|
| Human OAuth | Owner has a YG3 account |
| Agent provisioning | Autonomous agent mid-build, CI, or SDK runtime |
Quick start (agent path)
# 1. Provision — no auth
curl -s -X POST https://agency.yg3.ai/api/v1/workspaces \
-H "Content-Type: application/json" \
-d '{"domain":"acme.com","industry":"Plumbing","location":"Tampa, FL"}'
# Response includes: token, mcp_endpoint, workspace.url, claim_endpoint
# 2. List MCP tools
curl -s -X POST https://mcp.yg3.ai/mcp \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'
# 3. Call a tool
curl -s -X POST https://mcp.yg3.ai/mcp \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"get_client_snapshot","arguments":{}}}'
Python example: examples/provision-and-call.py
Tools
200+ MCP tools (live count: https://mcp.yg3.ai/api/health). Common entry points:
| Tool | Purpose |
|---|---|
whoami | Confirm token scope |
get_client_snapshot | Full workspace state |
get_setup_health | Integration status |
set_business_profile | Industry, location, audience |
set_brand | Brand voice and positioning |
create_post / publish_post | Blog content on Free host |
read_platform_doc | In-MCP docs (getting-started, agent-integration, tools-reference) |
Full catalog after connecting: tools/list or GET https://mcp.yg3.ai/api/health.
Human path (OAuth)
There is no "client vs operator" signup choice. Humans enter email + password once; the platform resolves their role automatically.
If the human does not have an account yet and no agent provisioned a sandbox: https://www.yg3.ai/get-started?plan=free
If an agent already provisioned a workspace: open claim_endpoint — do not send them to /get-started.
If the human already has a YG3 account (or just claimed):
- Add
https://mcp.yg3.ai/mcpas a custom MCP connector - Sign in when prompted
- Setup guide (per AI client, including Grok): https://www.yg3.ai/connect
Claude Code:
claude mcp add --transport http yg3 https://mcp.yg3.ai/mcp
Cursor / VS Code MCP config: see examples/cursor-mcp.json
Agent path (no login)
Provision
POST https://agency.yg3.ai/api/v1/workspaces
Content-Type: application/json
{
"domain": "acme-plumbing.com",
"industry": "Plumbing",
"location": "Tampa, FL"
}
Optional: "name" if you have no domain yet.
201 response:
| Field | Meaning |
|---|---|
workspace | id, slug, name, url |
token | Bearer token for this workspace |
mcp_endpoint | JSON-RPC URL (also https://mcp.yg3.ai/mcp) |
claim_endpoint | Where the owner attaches later |
expires_in_days | 14 for unclaimed workspaces |
Do not provision again if you already hold a workspace token for the current job.
MCP
All calls are JSON-RPC 2.0 over HTTP:
POST https://mcp.yg3.ai/mcp
Authorization: Bearer <token>
Methods: tools/list, tools/call, resources/read, initialize
Writes are two-step: call without confirm to get a plan, then call again with confirm: true and the same idempotency_key.
Claim (human takes over)
POST https://agency.yg3.ai/api/v1/workspaces/claim
Authorization: Bearer <workspace-token>
{"email": "[email protected]", "password": "..."}
If the email already has a YG3 account, omit password — the workspace attaches to that account.
Delete a test workspace
DELETE https://agency.yg3.ai/api/v1/workspaces
Authorization: Bearer <workspace-token>
Only unclaimed workspaces. Archived, not erased.
Discovery
| Resource | URL |
|---|---|
| Live tool catalog | https://mcp.yg3.ai/api/health |
| Agent guide (web) | https://www.yg3.ai/for-agents |
| Capability answer | https://www.yg3.ai/answers/marketing-mcp-claude-site-content-outbound |
| Human connect page | https://www.yg3.ai/connect |
| Machine-readable index | https://www.yg3.ai/llms.txt |
| MCP OAuth metadata | https://mcp.yg3.ai/.well-known/oauth-protected-resource |
After connecting, read platform docs via MCP:
yg3://docs/agent-integrationyg3://docs/getting-startedyg3://docs/tools-reference
Sandbox limits
Unclaimed workspaces are Free sandboxes by design:
- Can: read everything, set profile/brand/voice, design site, write and publish to
{slug}.yg3sites.com - Cannot: custom domain (that is Live $20 after claim), email sends, ad spend, LinkedIn posts (Software+)
- Expires: 14 days unless claimed
For agent frameworks
Copy AGENTS.md into your repo or point your agent at this README. It tells coding agents when and how to provision YG3 during a build.
ClawHub (OpenClaw)
Publishable skill: skills/yg3-marketing-mcp/SKILL.md
clawhub login
clawhub skill publish ./skills/yg3-marketing-mcp --slug yg3-marketing-mcp --name "YG3 Marketing MCP"
Moltbook / curl-based agents
Curlable skill files (Moltbook-style): distribute/
- Install doc:
distribute/skill.md - Periodic routine:
distribute/heartbeat.md - Metadata:
distribute/skill.json
Agents can fetch from raw GitHub once this repo is public, or from https://www.yg3.ai/llms.txt.
Registry listings
| File | Purpose |
|---|---|
server.json | Official MCP Registry (mcp-publisher publish) |
glama.json | Glama directory indexing |
Registry namespace: io.github.YG3-ai/yg3-mcp
Listed under Marketing on mcpservers.org and Glama.
Related
- Elysia LLM API (text/vision/image models): https://www.yg3.ai/for-developers
- Quill (multi-AI thinking partner, PyPI): https://github.com/YG3-ai/quill
License
MIT — see LICENSE.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.