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?
Beyond annotations (idempotentHint, non-destructive), the description adds meaningful behavioral context: it explains that calling with no args returns a link, that passing a token performs session-only login, and that config-based auth is permanent. It does not contradict 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 concise (three sentences), front-loaded with the core purpose, and clearly structured with 'Best:' and 'Or' to separate alternatives. Every sentence contributes value with no redundancy.
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 tool with one optional parameter, no output schema, and a user-interactive flow, the description covers all essential aspects: how to initiate login, what to do with the token, and the two authentication modes. It could mention the expected response or success criteria, but that is not critical given the simplicity.
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 lists an optional 'token' string with no description. The description fully compensates by explaining that 'token' is a JWT from the browser login and that omitting it yields the login link. This adds complete semantic meaning beyond the 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: authenticate an IDE agent to the MCP server via browser login and token acquisition. It uses specific verbs ('log in', 'copy the access token') and distinguishes itself from siblings like 'connect' by focusing on the authentication flow.
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 instructions for both permanent (config header) and session-only (token parameter) authentication, and explains when to call with no args. It lacks an explicit 'when not to use' or comparison to sibling tools, but the context is sufficiently clear.
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.
Most tools have distinct purposes: authenticate handles login, connect reports connection status, marketplace is a broad catalog/invoke hub, and the rest are utility functions. However, marketplace is overloaded and could be confused with toolkit_info or connect for status queries, and authenticate/connect overlap slightly.
Tool names follow no consistent pattern: single-word verbs (connect, marketplace, authenticate) mix with verb_noun underscores (report_bug, show_version, toolkit_info) and one long domain-specific name (transparencia_indicadores_pf_consultar) that breaks the style entirely.
Seven tools is a reasonable count, but the set is dominated by generic platform-management utilities, with only one domain-specific tool. For a server named 'Indicadores PF', the ratio feels disproportionate and many tools seem unrelated to the server's stated purpose.
The domain surface is severely thin: only a single consult operation for PF indicators, with no way to list available indicators, review history, or perform other related tasks. The platform tools don't contribute to domain coverage, leaving the set incomplete for its apparent purpose.