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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true and no destructive hint. The description adds behavioral context: it returns a link if called without args, and accepts a token for session login. It does not disclose potential side effects like token validation or expiration, but annotations already cover idempotency. No 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 three sentences long, each providing distinct information: purpose, permanent setup, and session usage. It is front-loaded and efficient, though slightly verbose. Still earns a 4.
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?
Considering the tool's simplicity and the absence of an output schema, the description covers the essential usage scenarios and token handling. It lacks details about return format or error handling, but for an authentication tool, the core guidance is present.
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?
Schema coverage is 0%, but the description explains the 'token' parameter as a JWT and specifies when to use it (after user pastes) vs calling without args to get a link. This provides necessary semantic meaning that the schema lacks.
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 login flow, token acquisition, and distinguishes between permanent config and session-only usage. Sibling tools are unrelated, so no confusion.
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 explicitly explains when to use this tool (for authentication) and provides two use cases (permanent via config header, session via token argument). However, it does not explicitly exclude scenarios or mention alternatives, though none are needed given the sibling tools.
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 distinct purpose with clear descriptions. The DataJud-specific tools (datajud_*) are well-separated from platform tools (authenticate, connect, marketplace, etc.), and even similar tools like datajud_get_processo and datajud_movimentos are differentiated by their scope.
Naming conventions are inconsistent: some tools are plain verbs (authenticate, connect), others are nouns (marketplace, toolkit_info), and the datajud_ prefix is applied to a mix of noun and verb phrases (datajud_movimentos vs datajud_get_processo). This lacks a predictable pattern.
With 10 tools, the count is within the typical range for a server. However, the inclusion of generic platform tools alongside domain-specific DataJud tools slightly dilutes the focus, though each tool serves a distinct role.
The DataJud domain coverage is adequate for common operations (login, search, fetch details, movements, raw query). The platform tools also cover essential actions like marketplace management and bug reporting. Minor gaps exist (e.g., no tool for listing available courts), but overall it's functional.