Search Reddit comments.
| Name | Required | Description | Default |
|---|---|---|---|
| pages | No | Number of pages to fetch, 1-10 (default: 1) | |
| query | Yes | Search keyword (max 500 characters) | |
| sort_by | No | Sort order: "most_recent", "relevance", or "top" | most_recent |
| get_sentiment | No | Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small per-page surcharge. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / pages / descriptionPrevious value: -"Number of pages to fetch, 1-5 (default: 1)"New value: +"Number of pages to fetch, 1-10 (default: 1)"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits itself, but it only repeats the operation. It does not mention output format, pagination behavior, rate limits, search semantics, or nuances of the get_sentiment option. The schema documents parameters but not behavior, so the agent gets no beyond-schema transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one short, front-loaded sentence with no filler or repetition. It is appropriately concise for a straightforward search tool, though it could have added context without becoming bloated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 4 parameters, no output schema, and no annotations, meaning the description is the main source of context beyond the schema. A single statement of purpose does not cover expected return data, sorting/pagination behavior, or how to choose between sibling search tools, so the definition is incomplete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; every parameter (query, pages, sort_by, get_sentiment) has a descriptive schema entry with defaults and constraints. The description adds no parameter information, but the baseline of 3 applies because the schema already carries the semantic load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource: 'Search Reddit comments.' It identifies the tool's function and, by naming comments rather than users or general Reddit content, hints at a distinction from siblings like search_reddit_users and search_reddit. However, it gives no scope details or contrasts, so it is clear but not fully differentiating.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to choose this tool over alternatives such as search_reddit, search_reddit_users, or search_forums. There are no conditions, exclusions, or mention of complementary tools, leaving the agent to infer usage solely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly scoped by platform and resource (e.g. search_twitter vs twitter_user_tweets vs twitter_tweet_details). A few pairs like twitter_tweet_comments vs twitter_user_replies or facebook_page_posts vs search_facebook_posts could cause minor confusion, but descriptions generally clarify the distinction.
The dominant pattern is snake_case with a platform_prefix_resource suffix, and search_* consistently marks search operations. Minor deviations include noun-style names like amazon_best_sellers and place_photos, and the odd get_ skill/comments tools, but the overall convention is predictable.
74 tools is far beyond the typical well-scoped MCP server, even for a multi-platform API aggregator. The breadth is justified by the many platforms covered, but an agent will face a very large action space, and this could reasonably be split into per-platform servers.
The server provides strong lifecycle coverage for its read-only domain: search, profile/details, posts, and engagement data across most platforms. Gaps exist for some platforms (e.g. no LinkedIn person profile, no Facebook event details, no Truth Social profile/search, no Reddit subreddit-specific tools), but the core workflows are well covered.