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Steam Review and Forum MCP

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JavaScript
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create_steam_review_corpus

Starts a server-side background Steam review fetch, stores results in a server-managed corpus, and returns an opaque ID for status checks, queries, and aggregates.

Instructions

Starts a server-side background review fetch, stores results in a server-managed corpus, and returns an opaque identifier immediately for later status checks, server-side queries, and aggregates. Data stays on the server and is not exported to the caller as files. Stored review records keep per-review metadata such as timestamps and playtime fields by default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appidYesSteam application ID
languageNoLanguage filter for the corpus fetch. Defaults to all languages.all
page_sizeNoSteam page size per fetch. Steam allows up to 100.
max_reviewsNoOptional cap for the background fetch. Use null to retrieve the full corpus.
review_typeNoReview polarity to retrieve. Defaults to all reviews.all
purchase_typeNoPurchase source to retrieve. Defaults to all purchase types.all
traversal_modeNoCursor traversal mode for exhaustive corpus retrieval. Use "recent" or "updated"; Steam's "all" helpfulness mode does not terminate reliably for full traversal.recent
chunk_size_reviewsNoHow many reviews to store per persisted chunk.
include_review_metadataNoWhen true, server-stored review chunks keep per-review metadata such as timestamp_created, timestamp_updated, timestamp_dev_responded, and author playtime fields like playtime_at_review and last_played, instead of only review text.
include_offtopic_activityNoWhen true, include off-topic/review-bomb activity in the corpus fetch.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.5

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 well: it discloses that the fetch is server-side/background, that the identifier is returned immediately, that data is not exported as files, and that per-review metadata is retained by default. It omits auth requirements, rate limits, and corpus lifetime/eviction, keeping it short of a 5.

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?

Three sentences, front-loaded with the action and return value, then two sentences of behavioral context. Nothing is redundant and each sentence carries distinct 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?

For a 10-parameter tool with no output schema and no annotations, the description covers the critical unknown an agent would have: what it returns (an opaque identifier) and where the data lives. It doesn't explain how to poll for completion, but that is delegated to get_steam_review_corpus_status.

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 all 10 parameters, including enums for language, review_type, purchase_type, and traversal_mode. The description's only parameter-linked value is reinforcing the metadata-retention default, which largely restates the include_review_metadata schema text, so baseline 3 applies.

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 names a specific verb chain (starts a background fetch, stores into a corpus, returns an opaque identifier) and pins the resource to Steam reviews. The async/corpus framing cleanly separates it from synchronous siblings like get_steam_review and from the status/query/aggregate tools it feeds.

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

Usage Guidelines3/5

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

The description implies the workflow (call this, then use the returned identifier for status checks, queries, and aggregates), which is genuine usage context. But it never states when to prefer this over get_steam_review or the forum-corpus sibling, and offers no exclusions or prerequisites.

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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