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 include idempotentHint=true and readOnlyHint=false. The description adds useful context about the two modes (permanent vs session-only) and the non-expiring nature of the config header, which goes beyond the raw annotation fields. It does not contradict any annotation.
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 front-loaded with the purpose. It could be slightly tightened, but each sentence contributes meaningful usage or behavioral detail, so it avoids fluff.
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 tool with one optional parameter and no output schema, the description covers both invocation patterns, the permanent vs session distinction, and how to obtain the link. It is complete enough for an agent to correctly use the tool without additional assumptions.
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?
With 0% schema description coverage, the description fully compensates by explaining the token parameter: it is a JWT to be pasted for session login, and omitting it means the agent should provide the login link. This gives clear semantic meaning to the single optional parameter.
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 this tool handles authentication for IDE agents: 'log in in the browser, copy the access token.' It distinguishes from sibling tools (connect, marketplace, etc.) by focusing on the auth flow and token setup.
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, actionable guidance: the best approach is adding a header to the server config for a permanent non-expiring connection, or pasting a token for session-only login. It also specifies that calling with no args returns the login link, so the agent knows exactly when to invoke each variant.
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.
Tools have distinct purposes: authentication, connection status, marketplace operations, bug reporting, version info, toolkit state, and a specific domain query. Some minor overlap exists between connect and toolkit_info (both report connection status), but generally an agent can choose correctly.
Naming is inconsistent: some are bare verbs (authenticate, connect), some are verb_noun (report_bug, show_version), some are nouns (marketplace, toolkit_info), and one is Portuguese with the verb at the end (trabalho_forcado_consultar). There is no uniform pattern across the set.
Seven tools is a reasonable number, but the server's name suggests a domain-specific scope (forced labor list), and six of the seven tools are generic platform utilities. The count feels imbalanced—too many meta-tools and too few domain tools relative to the apparent purpose.
The platform side is fairly complete (auth, status, marketplace, bug reporting, version, toolkit state), but the domain side is extremely thin: a single query tool for the dirty list, with no other operations like listing, batch checks, or historical data. For a server named after the domain, this is a significant gap.