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 goes beyond annotations (which already indicate non-read-only, non-destructive, idempotent) by explaining the login flow, the distinction between permanent and session-only logins, and the behavior when called with or without arguments. It does not explicitly mention side effects like modifying server config, but it alludes to adding the token to config, and there is 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 information-dense and relatively concise, packing the login funnel, token handling, and both invocation modes into two sentences. It is slightly run-on and could be cleaner, but every clause serves a purpose and the structure is front-loaded with the tool's core 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?
For an authentication tool with no output schema, the description covers the essential workflow: how to log in, how to provide the token, and the no-args behavior. It lacks explicit detail about the return value (though 'get the link' is mentioned) and does not mention error cases, but the information provided is sufficient for an agent to invoke the tool correctly in most contexts.
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?
Although the schema has only a single optional 'token' parameter with 0% description coverage, the description fully explains its semantics: it is a JWT to be pasted for session-only login. It also clarifies the behavior of calling with no args (returns the login link). This fully compensates for the schema's lack of description.
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 to MCP.AI for IDE agents. It uses the specific verb 'log in' and describes the resource (MCP.AI for IDE agents), and its distinction from sibling tools (e.g., connect, show_version) is implicit but sufficient.
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 explicit usage guidance: the preferred method (adding the token as a header in the server config) and an alternative (session-only login via pasting the token). It explains when to use each approach, which is more than a vague 'use this tool for X.' It does not explicitly compare to sibling tools, but the internal alternatives are 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 clearly distinct purposes (authentication, connection status, marketplace, version, consultation). However, connect and toolkit_info both return connection-related status, creating slight overlap. Marketplace is a mega-tool with many sub-actions, but its description is thorough enough to avoid confusion.
Naming conventions are inconsistent: some tools are verbs (authenticate, connect, report_bug), some are nouns (marketplace, toolkit_info), and one is a Portuguese compound verb (sintegra_rs_consultar). There is no consistent verb_noun pattern, and the language mix further weakens predictability.
With 7 tools, the set is well-scoped for a platform management server. Each tool serves a distinct high-level function, and the count is within the ideal range without feeling bloated or sparse.
The tool surface covers core platform operations: authentication, connection status, marketplace interactions (search/invoke/install), bug reporting, version display, and toolkit state. Minor gaps exist, such as no explicit disconnect or dedicated credential management beyond what marketplace/connect offer, but agents can work around these.