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, idempotentHint, and destructiveHint, establishing this as a safe read operation. The description adds value beyond these by specifying exactly what data is returned (installed MCPs, their connection status, accounts, catalog tool counts), providing concrete behavioral context without contradicting annotations.
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, well-structured sentence that front-loads the verb and resource, then provides a compact list of return details. Every word contributes meaning, with no redundancy or filler.
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?
Given the tool has no parameters, no output schema, and simple read-only behavior, the description is sufficiently complete. It tells the agent exactly what the response will contain, which is all that is needed for selection and 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?
The tool has no parameters, so the schema covers everything with 100% coverage. Per the rubric, a 4 is the baseline for zero-parameter tools because there is no parameter ambiguity to clarify.
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 uses the specific verb 'Returns' and clearly defines the resource as 'current toolkit state', enumerating exact contents (installed MCPs, connection status, connected accounts, catalog tool counts). This distinguishes it from siblings like 'show_version', which likely only reports a version number.
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 implies the tool is for inspecting the overall toolkit state, and the read-only nature is clear from annotations. However, it does not explicitly state when to choose this over alternatives like 'show_version' or 'connect', so it misses explicit exclusions or alternative 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.
Most tools have clearly distinct purposes: apf_rural_consultar is the only domain-specific query, while the rest are platform management functions. Slight overlap exists between connect and toolkit_info (both report connection status) and marketplace is a broad catch-all, but detailed descriptions make misselection unlikely.
Naming is inconsistent: apf_rural_consultar uses a snake_case domain prefix, while others are single verbs (authenticate, connect) or nouns (marketplace, toolkit_info). No consistent verb_noun pattern; styles are mixed.
Seven tools is within a reasonable range, but the server mixes one domain-specific tool with six generic platform utilities, making it feel bloated relative to the 'APF Rural' label. Not excessive, but the scope is broad.
The APF Rural consultation tool covers all expected lookup methods (CPF, CNPJ, number, CAR), and the platform tools provide authentication, status, marketplace access, and feedback. Minor gaps exist (e.g., no detailed history beyond the single query), but core workflows are covered.