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?
Annotations provide idempotentHint=true and destructiveHint=false. The description adds meaningful behavioral context by explaining the two operation modes (permanent header config vs session-only token) and that calling with no args yields a link. This goes beyond what annotations alone convey, with no 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 three sentences, front-loaded with context about the tool's audience and purpose. Each sentence delivers distinct value: purpose, recommended permanent method, and alternative session method. It is dense but not verbose, with no wasted words.
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?
The description thoroughly covers the tool's use cases and token parameter. However, it does not specify what the tool returns for either call mode (e.g., link, success message, error details). Since there is no output schema, this is a notable but minor gap for an otherwise simple 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 no description. The description clarifies that 'token' is a JWT to be pasted after user login, and that it is optional since calling with no args retrieves a link. This compensates well for the 0% schema description coverage.
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 identifies the tool's purpose: authenticating with MCP.AI for IDE agents. It specifies the verb (log in/authenticate), the resource (MCP.AI), and provides scope by detailing two authentication methods. Although it doesn't explicitly contrast with sibling 'connect', the unique focus on token-based authentication distinguishes it effectively.
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 gives explicit usage instructions: call with no args to get a link, call with { token: "<jwt>" } for session login, and recommends adding the token to server config for a permanent connection. It does not explicitly state when not to use this tool versus siblings, but the contextual guidance is strong.
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.
Each tool serves a distinct function: authentication, connection status, marketplace operations, bug reporting, version info, toolkit state, and the CEIS lookup. There is minimal overlap, and descriptions are clear enough to prevent misselection.
Tool names follow inconsistent patterns: some are bare verbs (authenticate, connect), some are verb_noun (report_bug, show_version), some are nouns (marketplace, toolkit_info), and one is a Portuguese noun-verb combination (ceis_consultar). This mixed convention and language creates a lack of predictable naming.
The count of 7 tools is within the typical range, but the server is named after a specific domain (CEIS) and only one tool relates to it. The other six are generic platform tools, making the scope feel unfocused and the count somewhat inappropriate for the apparent purpose.
For the CEIS domain, a single lookup tool covers the likely need (query registrant status). However, the server also includes unrelated platform management tools, and there are no other CEIS-related operations (e.g., history, details, bulk checks), so the surface is thin and not fully developed for the stated domain.