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?
Beyond the annotations (idempotentHint=true, readOnlyHint=false), the description discloses meaningful behavioral context: it triggers a browser login flow, the token is a JWT, the session-only login is non-permanent, and the recommended permanent path is via server config rather than the tool itself. This adds real value beyond structured 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?
Two sentences, front-loaded with the purpose ('log in in the browser, copy the access token'). The second sentence is a bit dense with multiple alternatives ('Best... Or... Or...'), but every clause earns its place and nothing is redundant.
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 1-parameter tool with no output schema, the description covers the authentication flow, both usage modes, token format, and the no-args behavior. Minor gaps exist around return values or post-login confirmation, but the description is largely sufficient for correct tool 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?
With 0% schema description coverage, the description fully compensates by explaining the token parameter: it's a JWT pasted after browser login, optional, and used for session-only authentication. The schema merely defines it as a string, so the description carries the semantic weight.
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 function: authenticate an IDE agent with MCP.AI by logging in via browser and obtaining an access token. It gives a specific verb+resource and explains the two authentication modes, leaving no ambiguity about what the tool does.
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 gives explicit usage guidance for two scenarios: configuring the token as a header for a permanent connection, or passing it as a session-only token. It also explains the no-args behavior (get the link). It doesn't explicitly exclude alternatives or contrast with sibling tools like 'connect', but the mode-based guidance is clear and actionable.
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 are individually well-described, but `connect` and `toolkit_info` overlap heavily on connection/account status, and `authenticate`/`connect` both relate to login flow. The `marketplace` tool is also a broad catch-all, so an agent could reasonably misroute among these.
The names mix bare verbs (`authenticate`, `connect`), English verb-noun pairs (`report_bug`, `show_version`), noun phrases (`marketplace`, `toolkit_info`), and a Portuguese object-first verb (`cro_al_cadastro_consultar`). There is no consistent naming convention across the toolset.
Seven tools is not inherently excessive, but six of them are generic mcp.ai/platform utilities and only one is the actual `Conselho Regional de Odontologia` domain query. The server is therefore platform-heavy rather than well-scoped around its stated dental-registration purpose.
For a read-only official registry consultation, the single domain tool `cro_al_cadastro_consultar` covers the core workflow; CRUD operations are not expected for a government-sourced lookup. Minor gaps exist around query/credit status and domain-specific validation, but agents can likely work around them.