Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value by describing the returned data (MCPs, connection status, accounts, catalog tool counts), giving the agent a picture of what to expect. It does not need to repeat safety hints, and there are no contradictions.
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 description is a single, tightly written sentence that front-loads the primary action ('Returns') and then lists the concrete components. Every word earns its place; there is no redundancy or filler. Excellent conciseness.
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?
For a tool with no parameters, no output schema, and a straightforward read-only function, the description fully specifies the return value. It covers all the information an agent needs to decide to call it and interpret its result. Given the low complexity, this is complete.
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?
The tool has zero parameters, so the schema trivially covers 100% of parameters. Description adds no parameter semantics, but with no parameters there is nothing to clarify. Per rubric, the baseline for 0 params is 4, and no additional explanation is needed.
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 starts with the specific verb 'Returns' and clearly identifies the resource: 'current toolkit state'. It enumerates the exact contents (installed MCPs, connection status, connected accounts, catalog tool counts), which distinguishes it from sibling tools like authenticate or connect. This is a model of purpose clarity.
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?
The description conveys a clear context: this is the tool to inspect overall toolkit status. While it doesn't explicitly say 'use this when you need an overview' or exclude alternatives, the sibling tools (authenticate, connect, etc.) each have distinct actions, making the usage context obvious. A 4 is appropriate for clear context without explicit when/when-not guidance.
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.
The tools have mostly distinct purposes, but connect, authenticate, and toolkit_info overlap in connection/status reporting, which could cause confusion. The credit score tool is clearly unique, but the platform utilities blur together.
Naming mixes verbs (authenticate, connect, report_bug, show_version) with nouns (marketplace, toolkit_info) and includes Portuguese (credito_score_consultar). No consistent verb_noun pattern across the set.
The server is named 'Score de Crédito' but only one of seven tools relates to credit scoring; the rest are generic platform tools. The count is misaligned with the apparent domain, making the set feel padded with infrastructure utilities.
For a credit score server, the surface is severely incomplete—only a single query operation exists, with no history, analysis, or management features. The platform tools do not compensate for the lack of domain coverage.