Skip to main content
Glama

Social Fetch

by io.github.social-freak-ltd

List Reddit subreddit posts

reddit_subreddit_posts_list
Read-only

List a subreddit's post feed (hot/new/top, no keyword) — use reddit.subreddit.search.list to search within it by keyword. Returns a list (use cursor when paginated).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoOptional sort order for the returned posts.
cursorNoOpaque pagination cursor from a previous response.
contextYesDescribe the user's underlying goal in one sentence — not the tool you are calling.
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
subredditYesSubreddit name, optional `r/` prefix, or Reddit subreddit URL. Must match Reddit's exact casing. Lists posts for this subreddit.
timeframeNoOptional timeframe used only when `sort` is `top`. Ignored/rejected for other sorts.
conversation_idNoEcho the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Schema Changelog

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

  1. Changed5 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Describe the user's underlying goal in one sentence — not the tool you are calling.",
+  "type": "string"
+}
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "subreddit"
-]New value: +[
+  "subreddit",
+  "context",
+  "llm_model"
+]
  2. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. Changed1 schema field changed
    • changedInput schema / properties / timeframe / description
      Previous value: -"Optional timeframe used with time-based sort orders."New value: +"Optional timeframe used only when `sort` is `top`. Ignored/rejected for other sorts."
  4. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  5. Changed1 schema field changed
    • changedInput schema / properties / cursor / description
      Previous value: -"Opaque pagination cursor from a previous response (`data.page.nextCursor`)."New value: +"Opaque pagination cursor from a previous response."
  6. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavior beyond that: it clarifies the feed is hot/new/top with no keyword, that returns a list, and that cursor pagination is required. This gives more operational detail than a bare read-only declaration while not describing every edge case.

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 two sentences with no filler: the first sentence states the core behavior and the key alternative, and the second covers return type and pagination. It is front-loaded, easily scannable, and every clause adds decision-relevant information.

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?

The definition covers the essential call decision: feed listing vs keyword search, and pagination via cursor. With 100% schema coverage on seven parameters, an agent can correctly supply subreddit, sort, timeframe, and required fields. It lacks a detailed return shape, but no output schema exists and 'Returns a list' plus cursor guidance is a reasonable minimum for this read-only list tool.

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 description coverage is 100%, so the schema already documents every parameter, including sort enum, timeframe nuance, cursor semantics, and the uniusual context and llm_model fields. The description adds only minor reinforcement like 'no keyword' and 'use cursor when paginated', which maps onto existing schema descriptions. Baseline 3 is appropriate because the schema carries the heavy lifting.

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 states a specific verb, resource, and scope: 'List a subreddit's post feed' with hot/new/top, and explicitly notes 'no keyword'. It also distinguishes itself from the keyword-search sibling by directing agents to 'use reddit.subreddit.search.list to search within it by keyword', making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly says when to use this tool versus the alternative: use this for feed listing without a keyword, and use 'reddit.subreddit.search.list' when searching within the subreddit by keyword. It additionally gives pagination guidance ('use cursor when paginated'), so an agent knows how to continue iterating across pages.

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

All Social Fetch toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation5/5

Each tool is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.

Naming Consistency5/5

All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).

Tool Count2/5

The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.

Completeness4/5

The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.

Resources