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, the description discloses that config-based auth is permanent and non-expiring, while pasted tokens are session-only, and that no-args returns a login link. This adds meaningful behavioral context without contradicting the idempotentHint or destructiveHint 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 target audience and core action, and every sentence adds a distinct piece of guidance. It is compact yet complete.
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 single-optional-parameter auth tool with no output schema, the description covers the login flow, token handling, persistence options, and invocation patterns. No critical context appears missing.
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 optional 'token' parameter: it should contain the JWT for session-only login, and omitting it triggers link generation. This is more useful than a bare schema property.
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: logging into MCP.AI for IDE agents by browser login and access token. It is specific about the authentication flow, but it does not explicitly distinguish this from sibling tools like 'connect', so it falls short of full sibling differentiation.
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 modes: permanent config via Authorization header, session-only login by pasting a JWT, and no-args to retrieve the login link. It also indicates the recommended approach ('Best') and when to use each variant.
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 single domain tool is clearly distinct, but the platform tools overlap: `authenticate`/`connect` both relate to connection state, and `marketplace`/`toolkit_info` both describe installed or callable tools. The long descriptions help, but the boundaries are not crisp, especially since `marketplace` also bundles sub-actions like `report_bug` that exist as a standalone tool.
Names mix one-word verbs (`connect`, `authenticate`), noun-only names (`marketplace`), snake_case verb+object compounds (`report_bug`, `show_version`), and a long Portuguese-style domain name (`git_cidadao_pr_multas_consultar`). There is no consistent naming convention or language across the set.
Seven tools is a reasonable raw count, but the set is really six platform utilities plus one domain-specific fines query. For a server named after a specific Brazilian fines product, the tool list feels padded and not tightly scoped to the apparent purpose.
The core operation, consulting official Brazilian fine information, is covered by `git_cidadao_pr_multas_consultar`, and the generic utilities handle auth, status, and billing-related flows. However, there are no other direct domain operations, and managing prepaid credits or query history is left to the catch-all `marketplace` tool.