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 discloses key behavioral traits beyond annotations: it describes the interaction flow (opens browser, expects user to copy token), the two modes (permanent via config header vs session-only via token param), and the optional nature of the token parameter. The annotations indicate idempotentHint=true and readOnlyHint=false, and the description's emphasis on token-based login aligns with these cues.
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, dense paragraph that is front-loaded with the most critical information (authentication flow) and then details the two options. Every sentence adds value: the opening identifies the target, the middle explains the permanent option, and the end covers the session-only variant. No filler or redundancy.
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?
The tool is simple (one optional param, no output schema), and the description fully covers its behavior: what happens with no args, what happens with a token, and the recommended permanent setup. It also addresses prerequisites (browser login, copying token). The context signals show no complexity that requires additional disclosure.
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?
Schema coverage is 0% for the single parameter 'token', so the description must compensate. It does so by explaining the token's purpose (JWT for session-only login) and how to obtain it ('paste it here for a session-only login'). It also clarifies that calling with no args returns a link, which is additional semantics beyond the bare schema. Slight deduction because the description doesn't specify the token's format precisely beyond 'jwt', but it's sufficient.
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: authenticate with MCP.AI for IDE agents. It specifies the verb 'authenticate', the resource (MCP.AI), and the target audience (IDE agents like Cursor). It distinguishes from siblings like 'connect' by detailing the authentication flow (browser login, token copy, config or session-only login).
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 provides explicit usage guidance: it explains when to use this tool (for login), how to use it (login in browser, copy token, add to config or pass as token), and provides alternative options (permanent via config vs session-only via paste). It also implies when not to use it (when already authenticated permanently via config).
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.
Each tool has a fairly clear role, but the boundaries blur around `authenticate`, `connect`, and `marketplace`: all three deal with credentials, connection status, and running platform tools. The single DETRAN query tool is unique, but an agent could hesitate between using it directly and using `marketplace` to invoke a similar paid/one-off tool.
Naming conventions are mixed: the domain tool is a long Portuguese snake_case verb (`detran_ms_multas_flex_consultar`), while several Spanish/English short verbs (`authenticate`, `connect`, `marketplace`) and compound nouns (`toolkit_info`, `show_version`) are used. There is no consistent verb_noun or naming pattern across the set.
Seven tools is not an unreasonable number, but six are generic platform and housekeeping operations rather than DETRAN-focused functionality. For a server advertised as a DETRAN MS fine tool, the set is heavily weighted away from the domain and feels imbalanced.
The only actual DETRAN capability is a single `consultar` operation, which may handle basic fine consultation but leaves no room for related domain needs such as vehicle/plate context, fine details, or payment/preparation flows. The `marketplace` tool is an escape hatch to external tools, not a coherent native DETRAN domain surface.