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Influship MCP

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by Influship

semantic_search_creators

Read-only

Discover influencers and content creators by topic, audience, geography, niche, or content style using natural-language queries. Returns ranked creator profiles with follower count, engagement rate, and categories.

Instructions

Semantic discovery search for influencers/content creators using natural-language queries.

Use this only when the user asks to discover creators by topic, audience, geography, niche, content style, or campaign criteria (e.g., "fitness creators in NYC", "vegan recipe creators with high engagement", "tech reviewers who cover phones"). The query is matched against creator profiles, extracted facts, and visual style via hybrid vector search.

Do not use this for exact handles, usernames, or known creator names. If the user gives a specific platform and handle (for example "@niickjackson on Instagram"), use get_profile first. For rough name/handle lookup, use search_creators. For multiple known handles, use lookup_profiles. Semantic search can return lookalike or topical matches and is allowed to miss an exact username.

Examples:

  • User: "Find news creators with 1M+ followers" -> use this tool.

  • User: "Find creators in LA who make cinematic travel videos" -> use this tool.

  • User: "Pull @niickjackson on Instagram" -> use get_profile, not this tool.

  • User: "Is @niickjackson a fit for Pixel?" -> use get_profile first, optionally get_posts, then match_creators.

Returns a ranked list of creators (id, platform, username, follower count, engagement rate, top categories, evidence facts). Use the flat follower, engagement-rate, and verified fields to constrain results when the user gives concrete numeric constraints.

Use find_lookalike_creators instead when you want creators SIMILAR to known ones. Use match_creators when you want to SCORE specific creators against a brief.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
platformsNoPlatforms to search. Omit for all.
limitNoMaximum results to return.
creator_kindsNoOptional creator kind filter. Omit for no creator-kind filter.
min_followersNoMinimum follower count.
max_followersNoMaximum follower count.
min_engagement_rateNoMinimum engagement rate as a percentage from 0 to 100.
max_engagement_rateNoMaximum engagement rate as a percentage from 0 to 100.
verifiedNoWhen set, only return verified or unverified creators.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
resultsNo
countNo
okNo
not_foundNo
has_moreNo
next_cursorNo
suggested_followupsNo
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that it uses hybrid vector search and returns a ranked list with specific fields, which is consistent and enhances transparency.

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 relatively long but well-structured with sections and examples. It is front-loaded with the purpose and every sentence adds unique value, though slight reduction could be possible.

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 9 parameters fully covered by schema, annotations present, and output schema existing, the description still adds rich behavioral context, usage guidance, and examples, making it fully complete.

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 baseline is 3. The description adds value by clarifying the query parameter should not contain exact handles and explains how to use follower/engagement/verified params for constraints.

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 performs 'semantic discovery search for influencers/content creators using natural-language queries,' which is specific and distinguishes it from sibling tools like search_creators and get_profile.

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?

Explicitly says when to use (e.g., topic, audience, geography) and when not to use (exact handles), provides alternatives like get_profile, search_creators, lookup_profiles, and includes concrete examples.

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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