Wobbo Bobo Ops & Creative Sandbox MCP Server
Reads and writes the same Supabase Postgres tables the n8n workflow uses, exposed as resources and tools: browsing projects by status, fetching a project's full record, and managing the off-limits rules and hook-styles lists conversationally instead of through the Supabase SQL editor.
Lets you log TikTok view counts against a project and correlate best-performing results by creative direction, hook style, and video-gen model — the performance data behind the 100k-view MVP-exit decision.
Click on "Deploy 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., "@Wobbo Bobo Ops & Creative Sandbox MCP Serverlog 15000 views for project 42"
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.
Wobbo Bobo Ops & Creative Sandbox — MCP Server
A Model Context Protocol server that complements (not replaces) the n8n Stage 1+2 automation. The n8n workflow owns the always-on, Telegram-triggered pipeline; this server gives a conversational window into the same Postgres state, plus a sandbox for testing the Direction/Hook/Script agents without a full Telegram round-trip.
What it adds
A missing piece the n8n pipeline has no home for: logging TikTok view counts back against a project, and correlating performance by creative direction / hook style / video-gen model — the actual data your MVP-exit decision (100k views) depends on.
Conversational management of the off-limits rules and hook-styles lists (same Postgres tables the n8n workflow reads/writes), instead of the Supabase SQL editor.
A sandbox to call the Direction/Hook/Script agents directly and iterate on prompts, without waiting on a Telegram approval loop.
Related MCP server: General-Purpose MCP Database Server
Setup
cd mcp-server
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env
# edit .env: DATABASE_URL (same Supabase session-pooler string used in n8n),
# ANTHROPIC_API_KEY (same key used in the n8n Anthropic credential)Then run the schema addition once (Supabase SQL Editor):
cat schema.sqlRun it standalone (smoke test)
source .venv/bin/activate
python3 server.pyIt should sit waiting on stdio — that's normal, it's meant to be driven by an MCP client, not run interactively. Ctrl+C to stop.
Register with Claude Code
claude mcp add wobbobobo -- python3 /Users/eugeneshemchuk/DEV/n8n/mcp-server/server.py(Run claude mcp add --help if the flags above don't match your installed
version — the add subcommand's exact syntax has changed across releases.)
Register with Claude Desktop
Add to your claude_desktop_config.json (Settings → Developer → Edit Config):
{
"mcpServers": {
"wobbobobo": {
"command": "python3",
"args": ["/Users/eugeneshemchuk/DEV/n8n/mcp-server/server.py"]
}
}
}Restart Claude Desktop after editing.
What's exposed
Resources (readable data):
wobbobobo://off-limits-rules— active off-limits ruleswobbobobo://hook-styles— active rotating hook styleswobbobobo://project/{project_id}— a single project's full record
Tools:
list_projects(status?, limit?)— browse projects by statusget_project(project_id)— full detail on one projectlog_video_performance(project_id, views)— log a TikTok view countcorrelate_performance(group_by)— best-views breakdown by direction / hook_style / model_usedadd_off_limits_rule(rule_text)/deactivate_off_limits_rule(id)add_hook_style(style_name, style_description)generate_direction(idea, verdict?, reasoning?)— sandbox call to the Direction Agentgenerate_hooks(idea, direction_tone, visual_style, why_it_could_hit)— sandbox call to the Hook Agentgenerate_script(idea, direction_tone, visual_style, why_it_could_hit, hooks)— sandbox call to the Script Agentgenerate_script_edit(...)— sandbox call to the Script Agent's edit pass
Known tradeoff
The Direction/Hook/Script prompts here are copied from the n8n workflow's HTTP nodes, not shared from a single source. If you tune a prompt in one place, update the other by hand — there's no shared package linking them.
This server cannot be deployed
Maintenance
Related MCP Connectors
Read a project's prompts, logs and agents, and send new work to the agent on your own machines.
- OrbitOAuthio.orbitapps
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Analytical memory for AI agents: a real Postgres queried in plain English over MCP. One command.
Connect, monitor, and control AI agents — tasks, approvals, schedules, and governance.
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