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BuzzSearch MCP Server

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by buzzsearch

Get raw comments

get_comments

Fetch raw comment bodies from a completed search, grouped by thread or video. Filter by source, keyword, or minimum score, then page results with limit and offset.

Instructions

The raw comment bodies behind a completed search, grouped by thread or video, filtered and paged. Free. A search reads hundreds to thousands of comments, so filter by source, a substring, or a minimum score, and page with limit and offset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
sourcesNo
containsNoCase-insensitive substring filter on the comment body.
min_scoreNoMinimum upvotes or likes.
search_idYesThe search id returned by `search` or `list_searches`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.1

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses that results are grouped by thread or video, that paging is via limit/offset, and that the call is free (cost signal). It omits auth requirements, rate limits, and any indication of what happens on an invalid or expired search_id.

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?

Three tight sentences with the resource and its grouping stated first, followed by the filtering rationale. 'Free.' is a short standalone fragment but it carries real information, so little is wasted.

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?

There is no output schema, so the description usefully covers the return shape (comment bodies grouped by thread or video, paged). For a 6-parameter read tool with no annotations this is close to complete, lacking only permission/pagination-boundary details.

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 only 50%, so the description must compensate, and it does: it maps sources to filtering, contains to substring matching, min_score to a threshold, and limit/offset to paging. Only search_id is left entirely to the schema, which already documents it well.

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 names the resource (raw comment bodies), the scope (behind a completed search), and the organization (grouped by thread or video, filtered and paged). It is specific enough to act on, but it never names or contrasts itself with siblings like get_quotes or get_sources, so an agent must infer the boundary.

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?

It states the precondition (a completed search) and gives concrete decision support: since a search reads hundreds to thousands of comments, use source/contains/min_score filters and page with limit/offset. It stops short of explicit when-not or named alternatives, but the usage context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.