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?
Describes the behavior beyond annotations: no-arg call returns a login link, token call performs a session login, and configuration allows a permanent connection. This adds context to the annotations (idempotentHint=true, readOnlyHint=false) without contradictions.
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 only two sentences but is somewhat rambling, mixing configuration advice with direct usage instructions. It is informative but could be better organized and front-loaded.
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?
Covers the three usage scenarios (no args, with token, permanent config) and mentions the returned login link. Despite lacking an output schema, it provides enough detail for an agent to call the tool effectively.
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 an optional string with no description (0% coverage). The description clarifies the token is a JWT and explains both calling conventions (with token and with no arguments), effectively compensating for the schema gap.
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 explains the tool is for authenticating to MCP.AI by obtaining an access token via browser login or accepting a pasted JWT. It uses specific verbs and resources and conveys the core purpose, though it does not differentiate from sibling tools like 'connect'.
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?
Provides explicit guidance on when to use the permanent token configuration (via server config header) versus session-only login (passing the token), and mentions the no-args call to retrieve the login link. It gives clear context and usage modes, though it doesn't compare against 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.
The tools serve disparate purposes (platform management vs. a specific data query), and several overlap in function (authenticate, connect, toolkit_info) while others are unrelated to the server's stated psychology registry domain. Descriptions are verbose and mix languages, making it hard to distinguish when to use which tool.
Names are inconsistent, mixing English verbs (authenticate, connect, report_bug) with a Portuguese compound (cfp_cadastro_consultar) and some nouns (marketplace, toolkit_info). No clear pattern or convention is followed.
With 7 tools, the count is not excessive, but the mix of platform utilities and a single domain-specific query suggests the set is not cohesively scoped. The number feels arbitrary relative to the server's apparent purpose.
The toolkit lacks comprehensive coverage for the implied psychology registry domain; only cfp_cadastro_consultar addresses data lookup, and there are no CRUD or management operations for registrations. The platform tools do not contribute to domain completeness.