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Revuo

mcp.score_server

Read-only

Score an MCP server against the Revuo quality rubric. Pass either a product slug (scored from cached probe data on the product's direct-probe MCP entry; fast) OR an endpoint URL (probed live). Returns: { target, server, summary { coreAwarded/Max/Percent, extensionAwarded/Max/Percent, probedAt }, categories[] (ServerMetadata, CapabilityQuality, ConfigurationUX, RevuoExtensions), checks[] (every rubric check with awarded/max/passed/evaluated/fixSuggestion/evidence), topFixes[] (failed checks ranked by points-at-stake), probe (probe diagnostics) }. Core score (max 100) is Smithery-comparable. Extension score covers Revuo-specific signals (response time today; freshness, error envelope, schema stability are not yet implemented and report evaluated=false — excluded from totals, never counted as a failure). A check with evaluated=false is a Revuo gap, not the server's fault. Errors: { error: { code: 'bad_input'|'not_found', ... } }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoMCP endpoint URL (HTTPS) to probe and score. Mutually exclusive with slug.
slugNoProduct slug whose direct-probe MCP server to score. Mutually exclusive with url.
refreshNoWhen passing slug, force a fresh probe instead of using cached probe data. Default false.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
probeNo
checksNo
serverNo
targetNo
summaryNo
topFixesNo
categoriesNo

TDQS

A4.7/5.0
Behavior5/5

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

Adds significant detail beyond annotations: explains the return structure, that extension score has evaluated=false for unimplemented checks, and error codes. No contradiction with readOnlyHint and openWorldHint annotations.

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 well-structured and concise. It front-loads the purpose, then details parameters and return value in a clear, organized manner. Every sentence adds value without redundancy.

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

Completeness5/5

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

Given the tool has only 3 optional parameters and an output schema, the description is very complete. It explains the return fields, the evaluated=false nuance, and error handling. No gaps.

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 100%, so baseline is 3. The description adds value by explaining the mutually exclusive relationship between slug and url, and the effect of refresh. This helps the agent understand parameter semantics.

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 clearly states the tool scores an MCP server against a quality rubric, with two distinct modes (slug for cached, url for live). This distinguishes it from all sibling tools which are about listing, searching, or retrieving products/tools/categories.

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?

Explicitly explains when to use slug vs url, including that slug is fast (cached) and url is live. The refresh parameter is also explained. However, no explicit 'when not to use' is given, but the tool is well-scoped.

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

A4.4/5.0
Disambiguation4/5

The namespace grouping separates products, tools, taxonomy, and rankings cleanly, and each tool's description points to its intended query mode. Some overlap exists between products.search and products.find_by_capability, and between tools.search and tools.find_for_task, but the descriptions are detailed enough that an agent can usually pick correctly. categories.list and directory.overview also overlap, though directory.overview is explicitly marked as the preferred entry-point.

Naming Consistency4/5

The set follows a predictable `resource.action` dotted convention, with all-lowercase names and snake_case within actions. Minor deviations such as `directory.overview`, `tools.changes`, and `mcp.score_server` mix noun actions and verb+object phrases, but the overall pattern remains readable and easy to guess.

Tool Count4/5

14 tools is appropriate for a read-only directory covering products, capabilities, rankings, MCP setup, and tool discovery. The count is slightly high because the search/find family has several close variants, but each variant has a distinct query style and use case.

Completeness5/5

The surface covers the domain thoroughly: taxonomy, product search and details, capability lookup, agent-readiness scoring, rankings, MCP setup, tool discovery, and schema-drift detection. Cross-references such as products.get_mcp_setup supplying the hash consumed by tools.changes close the main workflow loops without dead ends.

Resources