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 non-read-only and non-destructive. The description adds the distinction between temporary session auth and permanent config auth, and mentions the token format (JWT). It does not disclose potential side effects like overwriting existing tokens, but given the tool's simple scope and annotation coverage, this is acceptable.
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 compact yet comprehensive, using two sentences to cover both invocation modes and the alternative config approach. No fluff, each clause adds value.
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 simple authentication tool with one optional parameter, the description covers all usage flows (no-arg link retrieval, token-based login, and config alternative). It fully prepares the agent for correct invocation without additional context.
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 description fully explains the single parameter: token is optional and used for session login, with no args retrieving a link. This adds meaningful meaning beyond the schema's minimal token type.
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: authenticate/login for MCP.AI IDE agents. It explicitly distinguishes the two modes (config header vs session token) and directs users to alternative behavior (config for permanent, tool for session), which separates it from sibling tools like 'connect' or 'report_bug'.
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?
Provides explicit usage guidance: call with no args to get a login link, or with a token for session-based auth. It also contrasts the tool-based approach with a permanent config-based alternative, making the decision context explicit.
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 marketplace tool bundles many capabilities—search, describe, invoke, install, subscribe, and even report_bug—which overlaps with the standalone report_bug tool. authenticate and connect also share an auth/connection boundary, so an agent could easily misselect among the meta-tools.
Tool names mix bare verbs (authenticate, connect), noun-style names (marketplace, toolkit_info), verb_noun names (report_bug, show_version), and a long Portuguese domain-specific name. There is no consistent naming convention across the set.
Seven tools is a reasonable count overall, but six of them are generic platform/admin tools while only one is domain-specific to the named Tribunal TRT purpose. The set feels like a small platform bundle with one query tool attached rather than a focused domain server.
The platform side is fairly complete with authentication, connectivity, versioning, toolkit info, bug reporting, and marketplace operations. The tribunal side is thin: only a single consultation tool exists, with no additional query modes or supporting operations, though a read-only official consultation may not require full CRUD.