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Influship Influencer Marketing MCP

Compare creator fit

render_creator_comparison

Use this when the user has 2–4 canonical creator IDs and a specific campaign brief. It fetches current creator details, scores each creator against the brief, and renders a side-by-side comparison. This may consume Influship account or API usage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional brand constraints or evaluation context.
creator_idsYesTwo to four canonical creator IDs to compare.
campaign_briefYesSpecific campaign, audience, product, and desired creator fit.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewYes
briefYes
titleYes
creatorsYes

TDQS

A4/5.0
Behavior3/5

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

Annotations are all false, providing no safety hints, so the description must disclose behavior. It adds a meaningful cost warning ('may consume Influship account or API usage') and states that it fetches current creator details, implying live data retrieval. However, it does not mention potential side effects (e.g., creating reports) or error behavior, so it carries only part of the burden.

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 three sentences, front-loaded with the usage condition, and every sentence adds value: the first gives when-to-use, the second describes the process, the third discloses resource consumption. No fluff or redundancy, making it appropriately concise for the tool's complexity.

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

Completeness4/5

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

An output schema exists, so return values need no explanation. The description covers the operational flow (fetch, score, render) and notes potential usage costs, which is sufficient for a moderate-complexity tool. It doesn't discuss edge cases like too many/few creators, but the schema's min/max constraints handle that, so the description is complete enough.

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% (all three parameters have descriptions), so baseline is 3. The description adds minimal extra meaning beyond the schema, such as 'canonical' and 'specific campaign brief', but these are also partly in the schema. It doesn't clarify parameter formats or relationships beyond what the 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 clearly states the tool's function with a specific verb ('renders'), a specific resource (creator comparison), and the process (fetches details, scores against brief). It distinguishes itself from siblings like render_creator_profile (single profile) by emphasizing comparison and scoring of 2–4 creators.

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 provides an explicit 'Use this when' condition with clear inputs (2–4 canonical creator IDs and a specific campaign brief). It doesn't mention alternatives or exclusion criteria, but the condition is concrete and actionable, which is sufficient for a clear context without needing to enumerate alternatives.

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