Influship Influencer Marketing MCP

get_posts

Read-only

Fetch a creator's posts, sorted and paginated.

Use this when the user asks to see what a creator has posted (e.g., "show me Jane's last 20 posts", "what are this creator's top-engagement reels?", "pull recent posts from creator-id ABC"). Identify the creator by either creator_id (UUID) OR (platform + username).

sort defaults to "recent" (newest first); use "top_engagement" for the highest- engagement posts, or one of "most_likes" / "most_views" / "most_comments" for a specific metric. limit defaults to 12 and is capped at 50. Pass cursor from a previous response's next_cursor to paginate.

Returns post records (caption, media URL, like/comment/view counts, timestamps), plus has_more and next_cursor for pagination.

Examples:

User: "Show @niickjackson's recent Instagram posts" -> use this tool with platform "instagram" and username "niickjackson".
User: "Is @niickjackson a fit for Pixel?" -> use this after get_profile when the fit analysis needs recent content evidence, then call match_creators.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`sort`	No	Sort order	recent
`limit`	No	Maximum posts to return
`cursor`	No	Opaque keyset cursor from next_cursor. A cursor is bound to the sort order that produced it; using it with another sort returns 400.
`platform`	No	Platform (required with username)
`username`	No	Username (required with platform)
`creator_id`	No	Creator ID (use this OR platform+username)

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

A4.7/5.0

Behavior5/5

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

Annotations already mark this as read-only and non-destructive, but the description adds substantial behavior: sort defaults and options, pagination via cursor, a limit cap of 50, cursor-sort binding (returns 400 if mismatched), and the output shape (caption, media URL, counts, timestamps, has_more, next_cursor). This goes beyond the schema and annotations.

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 front-loaded with the main verb and then delivers usage, parameter semantics, output, and examples in a structured way. Every section earns its place; the examples are particularly useful for an agent.

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 output schema exists and annotations declare read-only, the description effectively covers selection, invocation, pagination, and workflow context. It doesn't need to expand return fields because the output schema is present, and safety is covered by annotations.

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% with detailed parameter descriptions, but the description adds the creator identification pattern (creator_id OR platform+username) and explains sort/limit/cursor interplay in plain language with examples. This elevates it beyond schema repetition, though some content (cursor binding, sort formula) is already in the schema.

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 'Fetch a creator's posts, sorted and paginated,' a specific verb+resource+scope that clearly differentiates from single-post or profile tools. It reinforces with examples and workflow hints like 'use this after get_profile... then call match_creators,' distinguishing from sibling tools.

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 explicitly states when to use: 'Use this when the user asks to see what a creator has posted' with concrete examples. It also provides workflow context ('use this after get_profile... then call match_creators'), though it does not explicitly contrast with single-post siblings like get_instagram_post.

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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