MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
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?
The description explains the effects of both usage modes: permanent config change or session-based login. It implies state modification through config addition but does not explicitly state side effects or error handling, though annotations indicate idempotency.
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 verbose and wordy, repeating instructions and including unnecessary details like 'MCP.AI for IDE agents'. It could be condensed to a few sentences.
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?
It provides sufficient context for typical use, covering the two authentication paths and the token acquisition process. However, it lacks information about return values or error scenarios, which might be needed given no output schema.
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 single parameter 'token' is clearly described as an optional JWT, with instructions to pass it after the user pastes it, and the alternative of omitting it to get the link.
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 clearly states the tool's purpose: authenticating for IDE agents via browser login and token. It distinguishes from sibling tools by focusing solely on authentication.
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?
It provides explicit usage instructions: either pass the JWT token as an argument for session-only login, or add it to the server config for a permanent connection. It also explains that calling with no arguments returns the login link, covering both usage modes.
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 DETRAN query tool is clear, but `marketplace` is a meta-tool that overlaps with `connect`, `authenticate`, `toolkit_info`, and even `report_bug`. Since multiple tools can handle connection URLs, listing callable tools, reporting bugs, or running the same DETRAN query, an agent has ambiguous entry points for the same capability.
Names are mixed across styles: single tokens (`authenticate`, `connect`, `marketplace`), verb_noun (`report_bug`, `show_version`), and `detran_ms_multas_consultar`, which places the verb at the end. The set has no consistent naming convention, making the handful of tools feel more arbitrary than organized.
Seven tools is a reasonable raw number, but the the set is not well scoped: six are generic platform utilities and only one tool is actually DETRAN-specific. For a server named 'DETRAN MS: Multas', the real DETRAN surface is thin and the platform 'platform furniture' carries most of the tool count.
For the read-only consultation scope, `detran_ms_multas_consultar` covers the core operation, and the platform tools cover auth, connectivity, versioning, bug reporting, and marketplace access. Extra DETRAN workflows such as payment or appeals are not represented, but they are also not promised by the tool descriptions.