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 already provide idempotentHint=true and destructiveHint=false. The description adds context about session vs permanent connections and the mechanics of token delivery. It does not contradict annotations and discloses state-changing aspects (session login) beyond the structured data.
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 and front-loaded with the target audience. It packs a lot of essential information without wasted words, though it could be slightly more succinct by separating the config recommendation from the tool invocation details.
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 the tool has no output schema and multiple authentication paths, the description covers the main flows: permanent config, session token, and link retrieval. It does not cover error cases or post-authentication state, but it is reasonably complete 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?
Schema has one optional string 'token' with 0% coverage. The description compensates fully by explaining the token is a JWT for session-only login and that omitting it yields the login link. This adds meaning that the schema alone lacks.
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 authenticates IDE agents by logging in the browser and obtaining an access token. It distinguishes this from sibling tools like 'connect' or 'marketplace' by focusing specifically on authentication flow and token handling.
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 gives explicit usage scenarios: adding the token to server config for a permanent connection, pasting a session token, or calling with no args to get a login link. This provides clear when-to-use guidance and even explains the recommended approach over alternatives.
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 has a clearly distinct purpose: authentication, connection status, marketplace discovery/execution, bug reporting, version check, specific data consultation, and toolkit overview. No overlapping functions that would cause an agent to misselect.
Tool names follow no consistent pattern: single verbs (authenticate, connect), compound verbs (report_bug, show_version), a bare noun (marketplace), and a domain-specific descriptive name (sintegra_df_consultar). The mixture of styles makes it unpredictable.
7 tools is well within the ideal range (3-15) and each serves a necessary function for a server that manages platform connections and offers a specific data query. The scope is appropriately matched to the tool count.
The surface covers the core lifecycle: authentication, connection status, tool discovery/execution, billing management, feedback, version, and toolkit state. A minor gap such as no explicit disconnect or logout is non-critical, but the main workflows are supported.