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?
Adds behavioral context beyond annotations by explaining that no args returns the login link, while a token enables a session-only login, and suggests a permanent config approach. Does not disclose token replacement or error behavior, but idempotentHint and lack of destructiveHint provide safety context. No contradiction with 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 moderately sized and well-structured: it states the purpose, gives a best practice, then offers an alternative. Each sentence adds value, though it could be tightened slightly without losing information.
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 simple one-parameter tool with no output schema, the description covers invocation modes and purpose well. It implies the return value ('get the link') but does not specify response format or error scenarios. Overall, it is sufficiently complete for an AI agent to use correctly.
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 provides no description for 'token' (0% coverage), but the description fully compensates by explaining it as a JWT for session login and specifying that omitting it returns the login link. This gives clear meaning beyond the bare 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: authenticating to MCP.AI by either returning a login link (when called with no args) or accepting a JWT token for session login. It is specific about the resource and action, though it does not explicitly distinguish from the sibling 'connect' tool.
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 usage modes: 'Best: add it to this server's config as a header... Or paste it here for a session-only login' and clarifies when to call with no args versus with a token. It does not mention tool-level alternatives, but the guidance is clear and actionable.
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 core enrichment tool is distinct, but there is overlap among the platform tools: connect and toolkit_info both report connection status, and authenticate is also related to connection setup. An agent could confuse which tool to use for checking connectivity or managing credentials.
Tool names are inconsistent in style: single verbs (authenticate, connect), a Portuguese noun-verb phrase (enriquecimento_lead_consultar), generic nouns (marketplace), and verb_noun pairs (report_bug, show_version). There is no predictable convention across the set.
Seven tools is within a reasonable count range, but the set mixes one domain-specific tool with several generic platform management tools, making the overall scope feel unbalanced. The count itself is appropriate, though not perfectly scoped.
The lead enrichment domain is severely under-covered: only one tool (enriquecimento_lead_consultar) performs enrichment, with no support for other identifier types, batch operations, or lead lifecycle management. The platform tools are generic and do not address the server's stated purpose.