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 behavioral aspects beyond annotations, such as persistence (permanent vs. session) and the need for user input (pasting token). It doesn't explicitly mention potential side effects, but annotations already indicate it is idempotent and not read-only, so the description adds useful context without contradiction.
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 concise and well-structured, fitting into three sentences. It avoids redundancy and clearly separates the two use cases. The structure flows logically from general purpose to specific instructions.
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 description is complete enough for the tool's purpose. It explains the authentication process and the two ways to use it, but does not specify the return value or what happens after successful login (e.g., whether a session is established). This is acceptable given there is no output schema, and the tool name 'authenticate' makes the outcome implicit.
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 sole parameter 'token' is explained as a JWT, and its optional nature is clarified by describing two calling patterns (with token for session login, without for obtaining the link). This adds meaningful detail beyond the schema's basic type and optionality.
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: authentication for MCP.AI IDE agents. It explains the two main workflows (permanent config vs. session login) and is unambiguous about the action (log in, get token).
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 guidance on when to use each mode: 'Best: add it to this server's config... for a permanent, non-expiring connection' and 'Or paste it here for a session-only login.' It also explains the argument variations (with token vs. no args).
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.
Tools are mostly distinct, but 'connect' and 'toolkit_info' overlap in reporting connection status, and 'marketplace' is a catch-all for multiple functions (search, describe, invoke, install, subscribe), creating potential ambiguity about which tool to use for a given task.
All tool names use snake_case consistently, but there is a mix of verbs (authenticate, connect, report_bug, show_version) and nouns (marketplace, toolkit_info, tribunal_tst_cndt_consultar). While readable, the inconsistency in part-of-speech is a minor deviation from a strict verb_noun pattern.
With 7 tools, the server fits well within the ideal 3-15 range. The number of tools is appropriate for the stated purpose of tribunal query and platform management without being excessive or too sparse.
The server covers core operations: authentication, connection status, tribunal query, version, and toolkit state. However, the 'marketplace' tool bundles many sub-actions (search, describe, invoke, install, subscribe) into a single tool, which could be considered a design gap for fine-grained control, but overall the domain is covered with no critical missing operations.