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, so the safety profile is clear. The description adds context about what the state includes (installed MCPs, status, accounts, tool counts) but does not disclose additional behavioral traits such as whether the state is cached, if it requires connectivity, or if it triggers any background refresh. This is acceptable but not rich.
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 sentence that front-loads the action ('Returns') and then provides a compact enumeration of the content. Every word earns its place with no redundancy or fluff.
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 an info tool with no parameters and no output schema, the description covers the key aspects of what is returned: installed MCPs, connection status, accounts, and catalog tool counts. It is complete enough for an agent to understand the tool's purpose and output. It could optionally mention that it reflects current live state, but that is implied.
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 provides no semantic burden. The baseline for 0 parameters is 4; the description does not need to add parameter details. It correctly focuses on the output rather than inputs.
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 names the resource 'current toolkit state', then enumerates the specific details: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like authenticate, connect, and show_version, which serve different functions.
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 clearly implies when to use the tool (when you need the toolkit state) and the scope of that state. It does not explicitly mention exclusions or alternatives, but the sibling tools are distinct enough that the purpose implicitly guides selection. A minor gap is the lack of explicit 'use when' or 'instead of' 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 tool set is a confusing mix of generic platform operations (marketplace, connect, toolkit_info, report_bug, show_version, authenticate) and one domain-specific tool (car_ambiental_rural_consultar). Several platform tools have overlapping or unclear boundaries: marketplace also lists installed tools, overlapping with toolkit_info; authenticate and connect both deal with authentication status. The single CAR tool stands out as unrelated to the rest, making it hard for an agent to know which tool to pick for a given task.
Tool naming is highly inconsistent: mixed languages (English 'authenticate', Portuguese 'car_ambiental_rural_consultar'), mixed casing (camelCase 'authenticate', 'marketplace' versus snake_case 'car_ambiental_rural_consultar', and multi-word compounds 'show_version', 'toolkit_info', 'report_bug'). There is no discernible verb_noun pattern or consistent style across the set.
While 7 tools is a reasonable count for a typical server, this server is named 'CAR' but only one of the seven tools actually relates to CAR. The other six are generic platform administration tools that would be expected in a completely different server (e.g., an MCP.AI toolkit management server). The count is thus inappropriate for the server's stated domain, as the majority of tools are out of place.
For a server ostensibly about CAR (Cadastro Ambiental Rural), the only domain tool is a single consult operation. There is no coverage for other plausible CAR workflows (e.g., listing properties, updating data, or exporting information). The remaining platform tools are unrelated to CAR, so the domain surface is severely incomplete. Even if the intended scope is solely 'consult,' the presence of many unrelated tools makes the completeness of the set as a whole poor.