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Influship Influencer Marketing MCP

search_creators

Read-onlyIdempotent

Find a creator by name/handle, while preserving legacy semantic creator search.

Use this as the default creator lookup tool when the user gives a creator-ish string but not a canonical creator UUID: a handle, partial handle, display name, creator name, or profile-ish text. This is cheap, fast, and backed by the creator lookup index.

If the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram"), prefer get_profile first because it returns the full platform profile. If you need to resolve a rough creator name or partial handle first, use this tool with query_type: "creator_lookup".

For backward compatibility, this tool still accepts the old semantic-search fields (platforms, follower/engagement filters, creator_kinds) and routes legacy calls to the semantic endpoint unless the query clearly contains a handle/profile URL. For new topical/niche discovery calls such as "fitness creators in NYC" or "vegan recipe creators with high engagement", prefer semantic_search_creators because its name is explicit and less likely to be confused with exact creator lookup.

Examples:

  • User: "Find @cris" -> use this tool with query "cris" and query_type "creator_lookup".

  • User: "Who is that fitness coach called Jane?" -> use this tool with query "Jane" and query_type "creator_lookup".

  • User: "Pull @niickjackson on Instagram" -> use get_profile with platform "instagram" and username "niickjackson".

  • User: "Find news creators with 1M+ followers" -> use semantic_search_creators, not this tool.

Returns either autocomplete-style creator lookup results or legacy semantic results, depending on routing. Use returned creator IDs with get_creator, find_lookalike_creators, or match_creators; use returned platform usernames with get_profile or get_posts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return.
queryYesNatural-language semantic discovery query by topic, niche, audience, geography, or content style. Do not pass exact handles or usernames here; use get_profile, lookup_profiles, or autocomplete_creators instead.
scopeNoWhich linked platforms to include in each lookup result.all_platforms
platformNoOptional platform to narrow username matching.
verifiedNoWhen set, only return verified or unverified creators.
platformsNoPlatforms to search. Omit for all.
query_typeNoUse creator_lookup for specific names/handles and semantic_discovery for topical/niche discovery. Auto routes exact handles and profile URLs to lookup, and keeps legacy semantic-search behavior otherwise.auto
creator_kindsNoOptional creator kind filter. Omit for no creator-kind filter.
max_followersNoMaximum follower count.
min_followersNoMinimum follower count.
max_engagement_rateNoMaximum engagement rate as a percentage from 0 to 100.
min_engagement_rateNoMinimum engagement rate as a percentage from 0 to 100.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive behavior, lowering the bar. The description adds significant transparency about dual routing, backward compatibility with legacy semantic fields, and conditional endpoint selection—none of which are visible from annotations or schema. There is no contradiction with the structured metadata.

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 comprehensive and front-loaded with purpose, but it is somewhat verbose—the 'cheap, fast, and backed by the creator lookup index' phrase adds little functional value. The example block is useful, though it could be tightened without sacrificing clarity.

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?

For a dual-mode tool with 12 parameters, the description covers primary use cases, routing behavior, return-value chaining, and sibling-tool boundaries. It thoroughly compensates for any schema ambiguity and gives the agent enough context to select and invoke the tool correctly, especially given the output schema exists.

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?

The tool description adds rich context for query usage (e.g., 'query "cris" with query_type "creator_lookup"') and explains how legacy fields are routed. However, the input schema's query description explicitly says 'Do not pass exact handles or usernames here,' which directly conflicts with the tool's primary purpose and creates contradictory parameter guidance for the agent.

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—'Find a creator by name/handle'—and explicitly frames it as the default creator lookup tool. It distinguishes itself from siblings like get_profile (exact handle lookup) and semantic_search_creators (topical/niche discovery), making its role unambiguous.

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?

It provides explicit when-to-use and when-not-to-use guidance: prefer get_profile for exact handles/platforms, use this tool for rough names or partial handles, and prefer semantic_search_creators for niche discovery. Concrete examples for each scenario reinforce the guidance, leaving little room for misinterpretation.

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