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 the two login modes (session-only vs permanent via header), clarifies that the token is a JWT, and indicates the behavior when called without arguments (returns a link). This goes well beyond the annotations and gives the agent a clear picture of expected behavior.
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 somewhat long but every sentence carries necessary information: audience, permanent vs session setup, and usage modes. It is structured logically and front-loaded with the main purpose.
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 there is no output schema and the tool's complexity is moderate, the description covers both invocation patterns and the distinction between permanent and session-only authentication. It does not mention response format, but that is likely not critical for an auth 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 only lists 'token' with a type, but the description elaborates that it should be a JWT string pasted by the user, and that omitting it will produce a login link. This adds substantial 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 this is an authentication tool for IDE agents, with a specific verb ('log in') and resource (access token). It distinguishes itself by explaining the login flow, making it unambiguous what the tool does.
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?
It provides explicit usage instructions: call with a token for session-only login, or with no args to get a link, and mentions adding the token as a header for a permanent connection. It does not explicitly compare with sibling tools like 'connect', but the context makes it clear when to use 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.
Most tools have clearly distinct purposes: authentication, connection status, marketplace, bug reporting, version info, and toolkit state. The domain-specific CAF tool stands apart. However, 'connect' and 'toolkit_info' both report connection status, which could cause minor confusion.
Naming is mixed: platform tools use single words or compound phrases like 'authenticate', 'report_bug', 'show_version', while the domain tool uses a prefixed snake_case pattern 'caf_agricultura_pf_consultar'. 'marketplace' and 'toolkit_info' are nouns rather than verbs, breaking the verb-based pattern.
Seven tools is a reasonable count, neither overwhelming nor too sparse. The platform tools are necessary for the MCP ecosystem integration, and the one domain tool addresses the core consultation need. Still, the server is heavily weighted toward platform utilities rather than CAF-specific functionality.
The CAF domain is covered only with a single consultation tool, which may be sufficient for a simple lookup service but lacks any additional operations like batch queries or result validation. The platform tools are complete for their purposes, so the overall set is functional but has minimal domain depth.