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?
Annotations already indicate idempotency and non-destructiveness, but the description adds valuable behavioral context: the distinction between permanent (config-based) and session-only (token-pasted) authentication, and the two invocation modes. It doesn't fully disclose response details, but it goes beyond the 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 three sentences, front-loaded with the tool's purpose and audience. Each sentence adds necessary information: purpose, recommended permanent setup, and alternative session setup. 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 single optional parameter, no output schema, and existing annotations, the description covers the main usage scenarios and flows. It lacks explicit return value details beyond the link for no-args calls, which is a minor gap but acceptable for an auth tool.
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 schema has a single 'token' property with no description, and schema coverage is 0%. The description explicitly explains the token parameter as a JWT to be pasted, and also explains that omitting it triggers the link retrieval behavior. This fully compensates for the schema's lack of detail.
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 authenticates to MCP.AI for IDE agents, with a specific browser login flow and token handling. It distinguishes itself from sibling tools by detailing the authentication mechanism and use cases.
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 when-to-use guidance: recommends adding the token to the server config for a permanent connection, or passing it to the tool for session-only login. It also clarifies that calling with no args returns the login link, giving the agent clear decision criteria.
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 tools are mostly distinct, but there is overlap between 'authenticate' and 'connect' (login vs status), and 'report_bug' duplicates functionality already inside 'marketplace'. The overloaded 'marketplace' tool bundles many sub-actions, making it harder to distinguish when to use it versus the dedicated tools.
Naming is inconsistent: English verbs ('authenticate', 'connect', 'report_bug', 'show_version') mix with noun-based names ('marketplace', 'toolkit_info') and a Portuguese snake_case domain tool ('cpf_cadastral_consultar'). No clear pattern is maintained across the set.
At 7 tools, the count is numerically reasonable, but only one tool ('cpf_cadastral_consultar') relates to the server's stated purpose. The other six are generic platform utilities that should likely live in a separate server, making the scope feel bloated for a 'Cadastro PF Básico' service.
The CPF domain surface is severely minimal: just a single consultation tool. There are no additional CPF-related operations (e.g., validation, formatting, status history), and the rest of the tools are unrelated to the domain, leaving the server incomplete as a focused CPF toolset.