Keyapi Pinterest Analysis

Discover and analyze Pinterest users, pins, boards, followers, and following — search users, retrieve profile information, explore pin libraries and board co...

Security Scan

The skill's files, required Node runtime, and single KEYAPI_TOKEN credential align with its stated Pinterest-analysis purpose; no disproportionate or unrelated privileges were found, though it persists credentials and API responses locally and allows an optional server override that you should verify before use.

Purpose & Capability

Name/description (Pinterest analysis) match the actual requirements and behavior: the skill needs node and a KEYAPI_TOKEN and calls a KeyAPI MCP server. There are no unrelated credentials or binaries requested.

Instruction Scope

SKILL.md instructs running scripts/run.js which lists tools, reads schemas, calls MCP tools, caches responses, and can auto-paginate. This stays within the stated purpose, but the tool persists API responses to a local cache and can save the API token to a .env file (the script will write .env). Also the client supports overriding the MCP endpoint via KEYAPI_SERVER_URL, which could redirect calls to an arbitrary server if misconfigured.

Install Mechanism

No download/install script from arbitrary URLs. It uses npm dependencies (package.json) — specifically @modelcontextprotocol/sdk — which is a normal package registry install. No extract-from-URL or non-standard installers were used.

Credentials

Only KEYAPI_TOKEN is declared as required and that is appropriate for an API-backed integration. The code also reads an optional KEYAPI_SERVER_URL (not listed in required.env) to override the server; this is legitimate but worth noting because it can redirect traffic to another endpoint if set.

Persistence & Privilege

always is false and the skill does not request elevated platform privileges. The script writes a .keyapi-cache directory and may write a .env file containing KEYAPI_TOKEN in the skill directory, persisting credentials and API responses locally. The skill can be invoked autonomously by agents (default), which increases blast radius if a token is present.

Assessment

This skill is coherent with its stated Pinterest-analysis purpose, but review the following before installing: 1) The skill will persist API responses into .keyapi-cache and may save your KEYAPI_TOKEN to a .env file in the skill directory — treat that token like a secret. 2) The code supports overriding the MCP endpoint via KEYAPI_SERVER_URL; ensure this is not set to an untrusted URL. 3) Installing runs npm install which will fetch @modelcontextprotocol/sdk from the npm registry — review that dependency if you need extra assurance. 4) Because the agent can invoke skills autonomously by default, avoid leaving a high-privilege token in environment variables if you do not want automated requests made. If any of these behaviors are unacceptable, do not install or remove the token/override before running.

Discover and analyze Pinterest users, pins, boards, and social graphs — from profile lookup and content inventory to follower and following network traversal.

This skill provides comprehensive Pinterest user intelligence using the KeyAPI MCP service. It enables user search and profile retrieval, pin library exploration, board collection browsing, and follower/following network analysis — all through a unified, cache-first workflow.

Use this skill when you need to:

• Search for Pinterest users by name or keyword
• Retrieve a user's profile details, follower count, and bio
• Browse a user's pin library
• Explore a user's board collections
• Traverse a user's follower list with cursor-based pagination
• Analyze a user's following list with bookmark-based pagination

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

Prerequisites

Requirement	Details
KEYAPI_TOKEN	A valid API token from keyapi.ai. Register at the site to obtain your free token. Set it as an environment variable: export KEYAPI_TOKEN=your_token_here
Node.js	v18 or higher
Dependencies	Run npm install in the skill directory to install @modelcontextprotocol/sdk

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

MCP Server Configuration

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

Server URL : https://mcp.keyapi.ai/pinterest/mcp
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 --platform pinterest --list-tools

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

Analysis Scenarios

User Need	Node(s)	Best For
Search users by name or keyword	search_users	Creator discovery, influencer prospecting
User profile details and stats	get_user_information	Profile audit, follower count, bio
User's pin library	get_pins	Content inventory, pin theme analysis
User's board collections	get_boards	Board taxonomy, niche focus areas
Follower list with pagination	get_followers_detail	Audience sampling, follower network research
Following list with pagination	get_following_detail	Interest mapping, network affinity analysis

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

Workflow

Step 1 — Identify Analysis Targets and Select Nodes

Clarify the research objective and map it to one or more nodes. Typical entry points:

• User discovery: Use search_users with a keyword → select a target user.
• Profile audit: Use get_user_information with username to retrieve profile details and extract the numeric userid.
• Content inventory: Use get_pins + get_boards with username for a full content snapshot.
• Social graph analysis: Use get_followers_detail + get_following_detail with userid for network traversal.

Two Parameter Naming Conventions

Pinterest endpoints use different parameter names depending on the endpoint:

Parameter	Type	Used by
username	String (display name/handle)	search_users, get_user_information, get_pins
entry	String (username or board path)	get_boards
userid	Numeric string (e.g., 125186202050495625)	get_followers_detail, get_following_detail

Obtain the numeric userid from the get_user_information response before calling get_followers_detail or get_following_detail.

get_boards — entry Parameter

get_boards uses an entry parameter (not username). This accepts a username (e.g., broadstbullycom) or a board URL path. Pass the username to retrieve all boards for that user.

get_followers_detail — Two Pagination Identifiers

get_followers_detail uses two separate identifiers:

• userid — the numeric user ID of the target user
• node_id — an internal node identifier used with cursor for multi-page traversal

For the first call, pass only userid. Subsequent pages require both node_id and cursor values from the previous response.

get_following_detail — bookmark Pagination

get_following_detail uses bookmark (not cursor) for pagination. Pass the bookmark value from the previous response to fetch the next page. Omit for the first call.

Step 2 — Retrieve API Schema

Before calling any node, inspect its input schema to confirm required parameters and available options:

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

# Examples
node scripts/run.js --platform pinterest --schema get_user_information
node scripts/run.js --platform pinterest --schema get_followers_detail

Step 3 — Call APIs and Cache Results Locally

Execute tool calls and persist responses to the local cache to avoid redundant API calls.

Calling a tool:

# Single call with pretty output
node scripts/run.js --platform pinterest --tool <tool_name> \
  --params '<json_args>' --pretty

# Force fresh data, skip cache
node scripts/run.js --platform pinterest --tool <tool_name> \
  --params '<json_args>' --no-cache --pretty

Example — search users:

node scripts/run.js --platform pinterest --tool search_users \
  --params '{"username":"interior design"}' --pretty

Example — get user profile:

node scripts/run.js --platform pinterest --tool get_user_information \
  --params '{"username":"tastemade"}' --pretty

Example — get user pins:

node scripts/run.js --platform pinterest --tool get_pins \
  --params '{"username":"tastemade"}' --pretty

Example — get user boards:

node scripts/run.js --platform pinterest --tool get_boards \
  --params '{"entry":"tastemade"}' --pretty

Example — get followers (first page):

# Pass userid from get_user_information response
node scripts/run.js --platform pinterest --tool get_followers_detail \
  --params '{"userid":"125186202050495625"}' --pretty

Example — get followers (subsequent pages):

# Pass node_id and cursor from previous response
node scripts/run.js --platform pinterest --tool get_followers_detail \
  --params '{"userid":"125186202050495625","node_id":"987654321","cursor":"cursor_from_previous_response"}' --pretty

Example — get following (first page):

node scripts/run.js --platform pinterest --tool get_following_detail \
  --params '{"userid":"125186202050495625"}' --pretty

Example — get following (subsequent pages):

# Pass bookmark from previous response
node scripts/run.js --platform pinterest --tool get_following_detail \
  --params '{"userid":"125186202050495625","bookmark":"bookmark_from_previous_response"}' --pretty

Pagination reference:

Endpoint	Pagination method	First call	Subsequent pages
get_followers_detail	cursor + node_id	Pass userid only	Pass userid + node_id + cursor from response
get_following_detail	bookmark	Pass userid only	Pass userid + bookmark from response
search_users, get_user_information, get_pins, get_boards	—	Single-call or server-managed	—

Cache directory structure:

.keyapi-cache/
└── YYYY-MM-DD/
    ├── search_users/
    │   └── {params_hash}.json
    ├── get_user_information/
    │   └── {params_hash}.json
    ├── get_pins/
    │   └── {params_hash}.json
    ├── get_boards/
    │   └── {params_hash}.json
    ├── get_followers_detail/
    │   └── {params_hash}.json
    └── get_following_detail/
        └── {params_hash}.json

Cache-first policy:

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

Step 4 — Synthesize and Report Findings

After collecting all API responses, produce a structured Pinterest intelligence report:

For user profile analysis:

1. Profile Overview — Username, display name, numeric user ID, bio, follower count, following count, monthly views.
2. Content Summary — Pin count, board count, content themes and categories.
3. Board Taxonomy — Board names, pin counts per board, topic diversity.
4. Pin Analysis — Pin type distribution (images, videos, articles), top engagement pins, recurring topics.

For social graph analysis:

1. Follower Profile — Sample follower demographics, active categories, engagement signals.
2. Following Footprint — Accounts followed, category interests, brand affiliations.
3. Network Signals — Follower-to-following ratio, audience quality indicators.

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

Common Rules

Rule	Detail
get_boards uses entry	Pass the username as the entry parameter (not username). The parameter name differs from other endpoints.
userid resolution	get_followers_detail and get_following_detail require the numeric userid. Obtain it from get_user_information response.
get_followers_detail pagination	First call: pass userid only. Subsequent calls: pass userid + node_id + cursor from the previous response.
get_following_detail pagination	Uses bookmark (not cursor) for pagination. Pass bookmark from the previous response.
Success check	code = 0 → success. Any other value → failure. Always check the response code before processing data.
Retry on 500	If code = 500, retry the identical request up to 3 times with a 2–3 second pause between attempts before reporting the error.
Cache first	Always check the local .keyapi-cache/ directory before issuing a live API call.

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

Error Handling

Code	Meaning	Action
0	Success	Continue workflow normally
400	Bad request — invalid or missing parameters	Check entry vs username vs userid usage; verify numeric userid format
401	Unauthorized — token missing or expired	Confirm KEYAPI_TOKEN is set correctly; visit keyapi.ai to renew
403	Forbidden — plan quota exceeded or feature restricted	Review plan limits at keyapi.ai
404	Resource not found — user may not exist or account is private	Verify the username; private accounts may have restricted data
429	Rate limit exceeded	Wait 60 seconds, then retry
500	Internal server error	Retry up to 3 times with a 2–3 second pause; if it persists, log the full request and response and skip this node
Other non-0	Unexpected error	Log the full response body and surface the error message to the user