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 explains behavioral details beyond annotations: calling with no args returns a link, calling with the token establishes a session, and the config approach yields a permanent non-expiring connection. It aligns with the idempotentHint annotation (repeated calls with same token have same effect) and does not contradict any 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 two sentences but somewhat dense, packing instructions for both config and session approaches. It is well-structured (purpose, best practice, alternative) and every sentence carries useful information, though it could be tightened slightly without losing meaning.
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?
Given the simple schema (one optional param) and no output schema, the description covers the main behaviors: how to get the link, how to use the token, and the difference between permanent and session auth. It does not specify exact return values for the token-call path or error cases, but it is sufficiently complete for a single-parameter authentication 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 input schema has one optional 'token' property with zero description (0% coverage). The description fully compensates by explaining that the token is a JWT pasted from the browser, used for session-only login, and that omitting it returns the login link. This adds crucial meaning beyond the raw 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 purpose: authentication for MCP.AI IDE agents via browser login and token usage. It distinguishes itself from siblings like 'connect' or 'marketplace' by focusing on the login/token flow. The verb 'log in' and resource 'access token' make the function unambiguous.
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 clear usage context: it explains the recommended permanent config method versus a session-only token approach, and indicates when to call with or without arguments. It does not explicitly compare itself to alternate tools like 'connect', but the usage scenarios are well-defined so an agent can decide when to invoke it.
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 platform tools (authenticate, connect, marketplace, toolkit_info) have overlapping responsibilities around auth, connection status, and available tools, making it unclear which to use for a given task. The single TSE tool is distinct, but the surrounding tool boundaries are fuzzy.
Names are inconsistent: single-word verbs (connect, authenticate), nouns (marketplace, toolkit_info), and one snake_case domain tool (titulo_votacao_consultar) with no shared pattern. A consistent verb_noun or verb_object format is missing.
Seven tools is a reasonable number, but the scope is muddled: six are generic MCP platform utilities, while only one addresses the server's stated TSE purpose. Most tools are unrelated to voting-title queries, so they do not earn their place in a TSE-focused server.
The TSE domain is served by a single query tool with no supporting operations (e.g., no history, no batch lookups, no formatting helpers), and the platform tools create a confusing meta-layer. The actual consultation surface is minimal, and the set feels incomplete for a dedicated TSE service.