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mcp-creator-profile-reader

by mambalabsdev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Read Influencer Profiles by Handle

read_influencer_profiles
Read-onlyIdempotent

Retrieve influencer profile details across seven platforms from handles or URLs, returning followers, engagement rate, bio, and business email in one row.

Instructions

Reads creator profiles on TikTok, Instagram, YouTube, Pinterest, Twitch, Threads, and podcasts from handles or profile URLs. Returns one flat row per creator with display name, follower count, following count, post count, engagement rate, verified flag, bio text, bio link, any public business email, a country guess with the method behind it, and a stable creator_id. Engagement rate is lifetime likes per post over followers, and the method is named on the row rather than implied. It reads profiles only: it does not follow the bio link, which is what Link in Bio Scraper and Newsletter Detector does. Every row carries row_status and error_reason. Charges $0.001 per run plus $0.006 per profile read, and $0.01 per Instagram bio fetch when one is needed. Contributes the public records it finds to a shared creator and agency pool that all users of this actor read from, so a later run reads what this one found; contribute_to_shared_pool is on by default and turning it off leaves the run reading the pool and writing nothing. Only public data already in the returned rows is contributed, nothing from your Apify account or your input, and a contribution is not charged. Requires an APIFY_TOKEN and consumes Apify credits. Read only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
handlesNoOne per line. A profile URL on any supported platform (https://www.tiktok.com/@name, https://www.instagram.com/name/, https://www.youtube.com/@name, a Pinterest, Twitch, or Threads profile, an Apple Podcasts show page, or a Spotify show), or platform:@handle (tiktok:@name). A bare @handle needs `platforms` and is looked up on each listed platform. One entry is a single run; a list is a batch. Duplicates are removed before any fetch.
us_onlyNoLaunch scope is US creators. A row whose country_guess is a known non US country is returned as an error row saying so. Rows with no country signal are kept. Uncheck to keep every country. Default: true.
platformsNoWhich platforms a bare @handle is looked up on. A full profile URL carries its own platform and ignores this. This actor does not search; pass the creators you want read. Supported: TikTok, Instagram, YouTube, Pinterest, Twitch, Threads, and podcasts. Not X, not Facebook pages, not LinkedIn.
batch_sizeNoRows fetched at once. Leave empty for the measured per platform default; the measurement is in the README. Higher is faster and, above the measured point, loses rows.
twitch_app_tokenNoOptional. An app access token for your Twitch client id (client credentials flow). Used only for Twitch reads, never stored or logged.
twitch_client_idNoOptional. Your own registered Twitch application client id. With `twitch_app_token` the Twitch reads use the official Helix API instead of the public web endpoint. Never a Mamba Labs credential.
escalate_on_blockNoOn by default. A profile fetch that comes back as a bot detection page is retried once over the residential proxy. On Instagram the bio, bio link, and following are read from the profile page over residential when the embed and the datacenter API did not carry them, and a page that comes back readable charges instagram-bio-fetch ($0.010). Uncheck it to never pay that event: a blocked profile then returns a labeled error row, and Instagram rows keep an empty bio and bio link on about half of the reads. Default: true.
contribute_to_shared_poolNoOn by default. Contributes the public records this run finds to a shared creator and agency pool that all users of this actor read from, so a later run reads what this one found. Only public data already in the returned rows is sent, never your Apify account, your input list, or your API keys, and a contribution is not charged. Set false to read the pool and write nothing. Default: true.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnly, idempotent, and non-destructive annotations, the description discloses pricing per run/profile/bio fetch, the shared-pool contribution side effect with its default and opt-out, residential-proxy retry behavior, error-row semantics, country-guess methodology, and the engagement-rate formula. This is far more than annotations alone provide, and there is no direct contradiction with them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but front-loaded with the core capability and return shape, and nearly every sentence adds a distinct behavioral fact. It loses one point because the shared-pool explanation is repeated with considerable overlap in both the description and the `contribute_to_shared_pool` parameter, making it slightly less concise than it appears.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 8 parameters, no output schema, and cross-platform variability, the description carries the full burden of explaining return values — and it does so: flat row fields, row_status/error_reason, error handling for US-only filtering and blocked profiles, pricing, and side effects. An agent has everything needed to invoke it correctly and interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the parameter descriptions are already detailed, so the baseline is 3. The description adds operational context around cost, defaults, and the shared pool, but it does not materially add new parameter-level semantics beyond what the input schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a precise verb and resource — reads creator profiles across seven named platforms — and enumerates the exact fields returned, including engagement rate and creator_id. It also explicitly names what the tool does not do (follow bio links, search), which distinguishes it from adjacent actors like Link in Bio Scraper and Newsletter Detector.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear operational context: pass handles or profile URLs, bare handles need `platforms`, and the actor does not search. It names alternatives for bio-link following and lists platform exclusions (not X, not Facebook, not LinkedIn). It stops short of an explicit 'use this when...' statement, so it is not a perfect 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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