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RoC MCP Server

RoC MCP Server

Remote
returnoncreators.comBusiness & Marketing0Updated 28w ago

About RoC MCP Server

RoC MCP Server provides TikTok Shop creator-commerce benchmarks and planning tools for brands. Its tools draw on RoC platform data to assess brand fit, estimate returns, and guide creator programs and launch readiness.

Key features

  1. 01Category GMV, AOV, and activation benchmarks
  2. 02Projected Return on Creators calculations
  3. 03Creator profiles and recruitment targets
  4. 04Content format and commission guidance
  5. 05Brand fit and TikTok Shop readiness analysis
  6. 06Creator program gap analysis and action priorities

Use cases

  1. 01Compare a brand's category performance benchmarks
  2. 02Estimate projected creator-program returns
  3. 03Set creator recruitment and commission plans
  4. 04Assess TikTok Shop launch readiness and next steps

MCP support

Exposes creator-commerce benchmark, calculation, and analysis tools to MCP clients, including category benchmarks, brand-fit analysis, and TikTok Shop readiness.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://roc-mcp-jvutdol4j-ro-ct-eam.vercel.app/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

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.

Tools

Details

From the project README

RoC MCP Server

Creator commerce intelligence for TikTok Shop brands — powered by Return on Creators.

Built on the Model Context Protocol, this server gives AI assistants real benchmark data from 100+ TikTok Shop brands and $20M+ GMV processed.

Tools

ToolDescription
roc_get_category_benchmarksMedian + top-quartile GMV, AOV, creator activation rates, and top content formats by category
roc_calculate_projected_rocCalculate projected Return on Creators multiple with vertical-specific coefficients
roc_get_creator_profileIdeal creator tier, engagement benchmarks, match scoring rubric, and recruitment targets
roc_get_content_formatsHighest-converting TikTok content formats ranked by GMV contribution
roc_get_commission_guidanceMarket-rate commission guidance with tiered structure and sample strategy
roc_analyze_brand_fitFull brand fit analysis — fit score, blockers, expected GMV range
roc_get_tiktok_shop_readinessReadiness score with prioritized action plan for TikTok Shop launch
roc_get_amplifier_fitCreator program gap analysis — constraints, projections, weekly priority actions

Categories Supported

beauty · cpg · fashion · wellness · home · supplements

Running the Server

HTTP (default)
npm install
npm start
# Server runs at http://localhost:3000/mcp
stdio
TRANSPORT=stdio npm start
Custom port
PORT=8080 npm start

Connecting to Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "roc": {
      "command": "node",
      "args": ["/absolute/path/to/roc-mcp-server/src/index.js"],
      "env": { "TRANSPORT": "stdio" }
    }
  }
}

Connecting via HTTP

Use any MCP client that supports Streamable HTTP transport:

http://localhost:3000/mcp

Response Envelope

Every tool response includes:

{
  "result": { ... },
  "confidence": "high",
  "dataSource": "RoC platform data — 100+ brands, $20M+ GMV processed",
  "dataAsOf": "2026-Q1",
  "disclaimer": "Estimates based on RoC platform benchmarks. Actual results vary by brand, execution quality, and market conditions."
}

Data Sources

Benchmarks sourced from:

  • RoC platform data (100+ brands, $20M+ GMV)
  • syncly.app TikTok Affiliate Playbook 2026
  • 360om.agency commission benchmark analysis
  • accio.com TikTok Shop US Top Categories 2025
  • redstagfulfillment.com AOV data 2025
  • marketingltb.com TikTok Shop Stats 2025

Data as of: 2026-Q1

License

MIT

mcp-name: io.github.sugar-co-dev/roc-mcp-server

Comments

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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.