YG3 MCP — agent integration
MCP serverAI & modelsyg3 gives your AI marketing abilities across content, SEO, outbound outreach, LinkedIn, and ads. Once added, your AI can take on these marketing tasks for you and set up its own sandbox with a single request.
Available today. Use it from your connected AI after setup.
Needs your own account with this service. Credentials stay encrypted.
After adding it, ask your AI to set up a sandbox and give it a marketing task to try, such as drafting content. See the item's repository for setup details.
Then ask your AI: use YG3 MCP — agent integration
What your AI can do with it
- Draft marketing content
- Optimize content for search engines
- Run outbound outreach
- Handle LinkedIn marketing tasks
- Create and run ads
- Set up a sandbox with a single request
From the project's README
As published by yg3-ai/yg3-mcp in README.md.
Connect autonomous agents to YG3 marketing operations: content and SEO, outbound email, LinkedIn, and paid ads.
No signup required for agent builds. One HTTP call provisions a sandbox workspace and returns a Bearer token for MCP.
| 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
197+ 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 subdomain |
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, create one first: https://www.yg3.ai/get-started?plan=free
If the human already has a YG3 account (or just signed up):
- 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": "owner@example.com", "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 |
| 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-tier sandboxes by design:
- Can: read everything, set profile/brand/voice, design site, write and publish articles to
blog-{slug}.yg3.ai - Cannot: custom domain, email sends, ad spend, LinkedIn posts
- 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
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.
Signals
- Last commit
- Sep 2026
Advanced
- Delivery
- yg3-mcp MCP server → your ahel gateway (mcp.ahel.ai) → every connected AI client.
- Catalog kind
- mcp-server
- Gateway key
io-github-yg3-ai-yg3-mcp- Source
- github.com/yg3-ai/yg3-mcp
- Hosted endpoint
https://mcp.yg3.ai/mcp