Influship Influencer Marketing MCP

get_creator

Read-only

Fetch the full record for a single creator by ID or exact platform username.

Use this when you already have either:

a canonical creator UUID returned by search_creators, semantic_search_creators, autocomplete_creators, or find_lookalike_creators; or
an exact platform+username pair such as platform "instagram" and username "niickjackson".

Pass include: ['profiles'] to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context.

Examples:

User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id.
User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use get_profile if profile metrics are the main need.
User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use get_profile/get_posts for platform-specific metrics and content if needed.

Use lookup_profiles for batch exact profile lookups.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	No	Creator unique identifier
`include`	No	Additional data to include in response
`platform`	No	Social platform for the username.
`username`	No	Public username or handle. A leading @ is accepted.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`ok`	No
`data`	No
`count`	No
`results`	No
`has_more`	No
`not_found`	No
`next_cursor`	No
`suggested_followups`	No

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the readOnly annotation, the description discloses key runtime behavior: how include: ['profiles'] behaves with UUID inputs, and how platform+username inputs resolve through the profile endpoint and return both profile and creator records. This materially helps an agent predict tool behavior.

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

Conciseness5/5

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

The description is well structured: purpose first, then usage conditions, parameter behavior, and concrete examples. Every section earns its place, and the bulleted examples make the two lookup modes immediately understandable.

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?

Given the 100% schema coverage, output schema presence, and readOnly annotations, the description covers everything needed to invoke the tool correctly: lookup modes, include behavior, example intents, and sibling alternatives. No critical gap remains.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantic guidance beyond the schema by explaining the id vs platform+username relationship, the effect of include with UUIDs, and the special platform+username resolution behavior.

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 opens with a specific verb and resource: 'Fetch the full record for a single creator by ID or exact platform username.' It clearly differentiates this tool from siblings like get_profile and lookup_profiles by naming them and stating the boundary.

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

Usage Guidelines5/5

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

Provides explicit 'Use this when...' guidance with concrete caller contexts: canonical creator UUID or exact platform+username pair. It also names alternatives and tells the agent when to prefer get_profile or lookup_profiles, which removes routing ambiguity.

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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TDQS

A3.8/5.0

Disambiguation2/5

Several tools have overlapping boundaries: autocomplete_creators and search_creators are described as near-equivalent fuzzy lookups, get_creator and get_profile both resolve exact platform+username input, and the Instagram/TikTok post helpers overlap with generic get_posts. The descriptions work hard to disambiguate, but an agent would frequently need to choose between two or three equally plausible tools.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern, such as get_youtube_video, search_creators, match_creators, and render_creator_profile. Minor inconsistencies exist: singular/plural variants (get_instagram_post vs get_instagram_posts), list_ vs get_ for video listing, and search_creators carrying legacy semantic behavior under a lookup-sounding name.

Tool Count2/5

Twenty-eight tools places the server in the 'too many' range, and the count is inflated by near-duplicates like autocomplete_creators/search_creators, get_creator/get_profile, and singular/batch transcript variants. Even with three social platforms and rendering helpers, the surface would be more focused around 18–22 tools.

Completeness4/5

The core influencer research workflow is well covered: handle resolution, batch lookup, semantic discovery, lookalikes, posts, transcripts, YouTube search, matching, and comparison rendering. Gaps are minor—there is no creator shortlist persistence or cross-platform comment support—but the main discovery-to-match path has no dead ends.

Resources

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