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 annotations (readOnlyHint=false, idempotentHint=true), the description explains that adding to config creates a permanent, non-expiring connection, and pasting a token gives session-only login. This discloses side effects and persistence behavior. It does not contradict 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 but somewhat rambling, with redundant instructions like 'log in in the browser, copy the access token' followed by detailed usage. It could be tightened, but the essential information is present and front-loaded.
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 tool with no output schema and one optional parameter, the description covers the primary behaviors: how to obtain the login link, how to use the token, and the distinction between permanent and session-only authentication. It lacks error handling or post-auth behavior, but that is not critical for this simple 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 only defines an optional 'token' string with no description. The description fully explains the parameter: providing it with a JWT authenticates for the session, while omitting it returns the login link. This is comprehensive compensation for zero schema coverage.
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: to authenticate IDE agents via browser login and access token. It distinguishes from siblings by focusing on authentication with token/cookie, whereas alternatives like 'connect' likely serve different connection purposes. However, it is somewhat verbose and mixes instructions with purpose.
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 instructions on two usage modes: permanent config header vs session-only token. It also states that calling with no args returns the login link. It does not explicitly contrast with sibling tools, but the usage context is clear.
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 clearly distinct purpose: authentication, connection status, marketplace catalog/execution, bug reporting, version info, toolkit state, and the data query. There is no overlap even though marketplace is complex; it is still separate from the others.
Naming conventions are mixed: English verbs (authenticate, connect), a noun (marketplace), verb_noun pairs (report_bug, show_version), noun_noun (toolkit_info), and a long Portuguese name (transparencia_servidores_consultar). No consistent pattern.
Seven tools is within a reasonable range for a server that includes platform infrastructure plus a data tool. The count is not excessive, though several tools are generic platform utilities rather than domain-specific.
The domain appears to be federal employee transparency data, but only one query tool exists (by CPF). Missing other obvious query types such as by name, agency, or a listing endpoint. The platform tools are complete for their purpose but don't contribute to domain coverage.