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Influencer Talent Agency Lookup MCP Server

by mambalabsdev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Look Up an Influencer's Talent Agency or an Agency's Roster

lookup_influencer_talent_agency
Read-onlyIdempotent

Find the talent agency behind influencer handles or profile URLs, or list an agency's public creator roster from its domain or name.

Instructions

Works in two directions. Creator to agency: pass creator handles or profile URLs and get one row per creator with the talent agency that represents them, its domain, its public contact, and agency_match_method (email_domain_exact, email_domain_parent, public_roster, bio_wording, or no_match with the email domains tried in error_reason). Agency to roster: pass agency domains or agency names and get one row per creator on the agency's public roster, with platform, handle, and profile URL. The agency list is seeded from 13 public directories and holds 143 agencies and 557 roster creators; coverage is partial and every row says how it matched. Supports TikTok, Instagram, YouTube, Pinterest, Twitch, Threads, and podcasts. Charges $0.001 per run plus $0.008 per row returned, $0.004 per agency roster page rendered in the headless browser when render_unreadable_pages is on and the rendered page comes back readable, 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.
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.
agency_namesNoAgency to roster by name when you do not have the domain. Exact or partial name match against the list.
agency_domainsNoAgency to roster: one domain per line (for example viralnation.com). Returns one row per creator on the agency's public roster.
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.
render_unreadable_pagesNoOff by default. Some agency roster pages build their talent grid in the browser and return an empty shell to a plain fetch, so the roster reads as empty. Turn this on to render those pages in a headless browser and read the roster from the rendered page. Charged per page rendered (event browser-render) to cover the browser compute, and only when the rendered page comes back readable. A page that answers with a bot challenge is recorded as blocked and is never rendered.
contribute_to_shared_poolNoOn by default. The run 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. Only public data that is already in your own output rows is sent: nothing from your Apify account, your input list, your API keys, or your own notes. Nothing is charged for a contribution. Turn this off and the run still reads the pool and writes nothing to it. 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds substantial behavioral context: cost per run and per row, shared pool contribution behavior, retry on bot detection, and rendering of unreadable pages. It also clarifies that contributions only include public data already in output, and that turning off the pool still reads it. No contradiction with annotations.

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 quite long but justified given the tool's complexity: two modes, multiple parameters, cost structure, shared pool behavior, and edge cases. It is front-loaded with the core purpose ('Works in two directions') and then systematically details each aspect. While verbose, every sentence adds value; it avoids redundancy.

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?

The description covers all necessary aspects: input formats, output row contents for both modes, cost breakdown, shared pool semantics, handling of bot detection, and parameter defaults. Since there is no output schema, the description explicitly describes the returned rows for each direction, making it complete for an agent to call correctly.

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%, so all parameters have detailed descriptions. The tool description adds context on how parameters interplay (e.g., the two modes, batch size measurement, escalate_on_block behavior) but does not fundamentally add meaning beyond what the schema already provides. The baseline for high schema coverage is 3, and the description does not significantly elevate it.

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 clearly states the tool's dual purpose: mapping creators to agencies and agencies to rosters. It uses specific verbs ('look up', 'get') and resources ('talent agency', 'roster'), and distinguishes the two directions explicitly. Although there are no sibling tools, the description is unambiguous about what the tool does.

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?

The description explains exactly how to use each direction: passing creator handles for creator-to-agency, and agency domains/names for agency-to-roster. It also provides context like 'This actor does not search; pass the creators you want read' and lists unsupported platforms. However, it does not explicitly compare to alternatives (there are none) or provide conditional 'when to use' guidance beyond the two modes.

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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