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Glama

instagram-scraper

Search Hashtag

get_hashtag

Search by hashtag on Instagram Billing per call: 1 Credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tabsNo`top` or `recent` or `clips`
hashtagNoHashtag
next_pageNoThe value of next_page for viewing the next hashtag list for next_max_id
next_max_idNoThe value of next_max_id for viewing the next hashtag list

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are present, and the description does not disclose whether the tool is read-only, any side effects, cost implications (though it mentions billing per call, which is not a behavioral transparency detail), or error patterns. The lack of annotation means the description should have provided this, but it didn't.

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

Conciseness3/5

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

The description is concise but includes an irrelevant billing note ('Billing per call: 1 Credits') that detracts from clarity. Structurally it's a single sentence, but the extra billing info is unnecessary for tool usage.

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

Completeness2/5

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

The description lacks essential context: output format, pagination usage, parameter relationships, and any prerequisites. With no output schema, the description should have explained what the tool returns, but it doesn't. This leaves the agent uncertain about how to interpret results.

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

Parameters2/5

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

The schema includes descriptions for all four parameters, but they are vague and potentially confusing. 'tabs' lists valid values; 'hashtag' is just the name; 'next_page' and 'next_max_id' have overlapping and unclear statements. The descriptions do not adequately clarify the parameters' roles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches by hashtag on Instagram, which is specific and distinguishes it from sibling tools that search by other criteria. However, it does not mention what the search returns (e.g., post list, metadata), so it's not fully explicit.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives, nor how to handle pagination with next_page and next_max_id. The description is minimal and offers no usage context.

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

C2.4/5.0
Disambiguation2/5

Many tools have overlapping or near-identical purposes (e.g., get_posts vs get_posts_username, get_reels_posts vs get_reels_posts_username). The distinction between get_post_info, get_post_info_v2, get_reel, and get_tv_info is unclear from descriptions alone. This will cause frequent misselection.

Naming Consistency2/5

Naming is inconsistent: suffixes like '_username', '_hd', '_v2', '_id' appear sporadically, and the same resource type is named differently (e.g., 'posts' vs 'post_info' vs 'reels_posts' vs 'tv_posts'). Some tools are meta (get_requests, get_server) and deviate from the data-focused pattern. Overall, no clear naming convention.

Tool Count2/5

With 40 tools, the set is overly large for an Instagram scraper. Many tools are near-duplicates differing only by input type (ID vs username), which could be consolidated. The count far exceeds the typical 3-15 range and feels bloated, though not extreme.

Completeness4/5

The tool set covers a comprehensive range of Instagram data: user info, posts, reels, TV, stories, highlights, comments, likes, followers, followings, hashtag/location/music search, and even server status. Despite some vague tools (get_additional_info, get_basic_engagement), it appears functionally complete for the domain.

Resources