keyapi-tiktok-shop-creator-discovery

Discover and analyze TikTok Shop creators — identify top-performing sellers, evaluate sales metrics, and understand audience demographics for commerce-focused creator partnerships.

This skill provides deep intelligence on TikTok Shop creators using the KeyAPI MCP service. Unlike standard influencer analysis, this skill is specifically scoped to the TikTok e-commerce ecosystem, surfacing creators' actual sales performance, GMV contribution, product promotion behavior, and follower demographics — data that is only available within the TikTok Shop commercial platform.

Use this skill when you need to:

• Find TikTok Shop creators who actively sell products in a specific category
• Evaluate a creator's sales track record, GMV output, and product promotion effectiveness
• Understand a creator's audience profile (age, gender, geography) for commerce targeting
• Monitor trends in creator sales activity and follower growth over time
• Compare multiple shop creators to select the best-fit commercial partners

author: KeyAPI license: MIT repository: https://github.com/EchoSell/keyapi-skills

Prerequisites

author: KeyAPI license: MIT repository: https://github.com/EchoSell/keyapi-skills

MCP Server Configuration

All tool calls in this skill target the KeyAPI MCP server:

Server URL : https://mcp.keyapi.ai
Auth Header: Authorization: Bearer $KEYAPI_TOKEN

Setup (one-time):

# 1. Install dependencies
npm install

# 2. Set your API token (get one free at https://keyapi.ai/)
export KEYAPI_TOKEN=your_token_here

# 3. List all available tools to verify the connection
node scripts/run.js --list-tools

author: KeyAPI license: MIT repository: https://github.com/EchoSell/keyapi-skills

Analysis Scenarios

Select one or more nodes based on the research objective.

author: KeyAPI license: MIT repository: https://github.com/EchoSell/keyapi-skills

Workflow

Step 1 — Identify the Creator and Select Nodes

Clarify the user's objective and determine which nodes to invoke. Typical entry points:

• Starting from a @handle: Always begin with search_shop_creator to resolve the creator_oecuid.
• Full creator audit: Use get_shop_creator_detail + get_shop_creator_sales + get_shop_creator_trends.
• Audience analysis: Use get_shop_creator_audience for demographic profile.
• Content-commerce analysis: Use get_shop_creator_videos to identify which content formats drive the most sales.

⚠️ Critical: Resolving creator_oecuid

The creator_oecuid is the unique identifier used by TikTok's commercial/e-commerce platform (OEC = Overseas E-Commerce system). It is required by all nodes except search_shop_creator.

Users will typically provide a creator's unique_id (@handle). Always call search_shop_creator first to obtain the creator_oecuid before making any other calls.

All endpoints require a region parameter (one of: US, DE, TH, MY, ID, PH, VN). Always include it in every call.

Step 2 — Retrieve API Schema

Before calling any node, inspect its input schema to confirm required parameters and valid values:

node scripts/run.js --schema <tool_name>

# Example
node scripts/run.js --schema get_shop_creator_sales

Step 3 — Call APIs and Cache Results Locally

Execute the required tool calls and persist all responses to the local cache.

Calling a tool (using scripts/run.js):

# Single call — result is cached automatically
node scripts/run.js --tool <tool_name> --params '<json_args>' --pretty

# Force a fresh call, skip cache
node scripts/run.js --tool <tool_name> --params '<json_args>' --no-cache

Example — find a shop creator by unique_id:

node scripts/run.js --tool search_shop_creator \
  --params '{"unique_id":"example_creator","region":"US"}' --pretty

Example — get creator sales data:

node scripts/run.js --tool get_shop_creator_sales \
  --params '{"creator_oecuid":"7494008088472553296","region":"US"}' --pretty

Cache directory structure:

.keyapi-cache/
└── shop_creators/
    └── {creator_oecuid}/
        ├── detail.json        # get_shop_creator_detail
        ├── sales.json         # get_shop_creator_sales
        ├── audience.json      # get_shop_creator_audience
        ├── trends.json        # get_shop_creator_trends
        └── videos.json        # get_shop_creator_videos
└── searches/
    └── shop_creators/
        └── {unique_id}.json   # search_shop_creator (keyed by unique_id for direct lookup)

Cache-first policy:

Before every API call, check whether a cached result already exists. If a valid cache file exists for the given creator_oecuid and node, load from disk and skip the API call.

Recommended call sequence:

1. search_shop_creator(unique_id, region)          → obtains creator_oecuid
2. get_shop_creator_detail(creator_oecuid, region) → profile overview and key KPIs
3. get_shop_creator_sales(creator_oecuid, region)  → product sales and GMV breakdown
4. get_shop_creator_audience(creator_oecuid, region) → audience demographics
5. get_shop_creator_trends(creator_oecuid, region)   → time-series growth and sales trends
6. get_shop_creator_videos(creator_oecuid, region)   → promotion video performance

Cover image processing:

After each API call, scan all response image URLs. If any URL's host matches echosell-images.tos-ap-southeast-1.volces.com, collect those URLs and call batch_download_cover_images in a single batch request. Replace the original URLs in your working dataset with the converted URLs returned by this node.

Step 4 — Synthesize and Report Findings

After collecting all API responses, produce a structured creator evaluation report:

1. Creator Commerce Profile — Name, @handle, follower count, total GMV, active product categories, and TikTok Shop tenure.
2. Sales Performance Analysis — Total items sold, GMV breakdown by product, top-selling products, video-driven vs. live-stream-driven revenue split.
3. Audience Intelligence — Age and gender distribution, top geographic markets, audience-product category alignment.
4. Growth and Trend Analysis — Follower growth trajectory, correlation between video/live activity and sales spikes.
5. Content-Commerce Effectiveness — Highest-converting video formats, average views per promotion video, CTR signals.
6. Partnership Recommendations — Best-fit collaboration formats (product seeding, affiliate, exclusive collab), risk signals (declining trends, audience mismatch), estimated deal value benchmarks based on GMV history.

author: KeyAPI license: MIT repository: https://github.com/EchoSell/keyapi-skills

Common Rules

author: KeyAPI license: MIT repository: https://github.com/EchoSell/keyapi-skills

Error Handling