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?
Goes beyond annotations by describing the flow: it returns a login link, accepts a pasted token, and differentiates between persistent and session-based auth. It clarifies side effects (e.g., setting headers in config) and explicitly states the result of calling with no arguments.
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 moderately long but efficient, packing multiple scenarios into two sentences. It could be split into bullet points for readability, but every clause adds essential information.
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 an authentication tool with no output schema and minimal parameters, the description covers all critical aspects: obtaining the token, persistence, and exact call patterns. It leaves no obvious gaps for an agent to misuse the 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 `token` as a string with 0% coverage, but the description fully explains its purpose (paste the JWT for session login) and contrasts it with the no-argument case. This compensates for the sparse schema.
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 function: authenticating IDE agents by logging in and handling access tokens. It distinguishes itself from siblings by specifying the exact flow and token/cookie usage, and provides a concrete example invocation (`{ token: "<jwt>" }`).
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?
Explains two usage modes (permanent config vs session-only) and shows how to call the tool with or without arguments to get a link. While it doesn't explicitly contrast with the sibling 'connect' tool, it gives clear actionable guidance on when to use this authentication method.
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 JUCESP query tool is clearly distinct from the meta/platform tools. The main ambiguity is only between authenticate and connect, but their descriptions define different responsibilities (credential acquisition vs. connection status reporting).
Naming is noticeably mixed: bare verbs (authenticate, connect), snake_case verb+noun forms (report_bug, show_version), noun-only names (marketplace, toolkit_info), and a Portuguese language domain-specific tool (jucesp_documentos_consultar). No unified convention is maintained.
Seven tools is a manageable count, but most of them are generic platform support tools (marketplace, report_bug, show_version) rather than JUCESP domain tools. The server feels functionally thin for a domain-capable MCP, even though it does not have a bloat problem.
The server exposes only a single domain operation for querying archived JUCESP documents, with no filtering, detail view, pagination, download, or lifecycle tools. Beyond that one query, the remaining tools cover infrastructure rather than the stated JUCESP use-case, so the domain surface is quite incomplete.