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 discloses important behavioral traits, such as the permanent vs. session-limited nature of tokens and that calling with no arguments returns a link. This adds context beyond the annotation hints (e.g., idempotentHint=true) and explains side effects, though it omits potential error handling or rate-limit information.
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 contains all necessary information but is presented as a run-on, slightly disorganized block. Key points like 'Best:' and 'Or paste it here' could be structured with clearer separation and front-loading, but no sentence is wasted.
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 all facets of usage: authentication flow, token handling, both invocation patterns, and the permanent vs. session distinction. It adequately equips an agent to use the tool correctly without ambiguity.
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?
Despite the schema having no property descriptions, the description thoroughly explains the optional 'token' parameter, its expected format (JWT), and the effect of omitting it. This fully compensates for the 0% schema coverage by providing essential semantic meaning.
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 via browser login and token retrieval, using specific verbs like 'log in' and 'copy the access token.' It uniquely identifies the tool's function and distinguishes between the two login modes, making its purpose unmistakable.
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 provides clear, step-by-step usage instructions, including two alternative methods (permanent config token vs. session-only token) and the exact payload format. However, it does not compare this tool to its siblings or explicitly state when to prefer an alternative, so it doesn't reach a 5.
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 ANVISA consultation tool is clearly distinct, but several platform tools overlap: authenticate and connect both concern connection/auth, and marketplace and toolkit_info both expose catalog/install state. Detailed descriptions help separate them, so misselection is possible but not constant.
Most tools use lowercase English single-word names, while the actual domain tool uses Portuguese snake_case (anvisa_processo_consultar). The set mixes languages and naming styles, with no consistent verb_noun pattern across the server.
Seven tools is not inherently too many, but six are generic platform infrastructure tools (auth, marketplace, version, toolkit state) and only one serves the declared ANVISA Processo purpose. The count is misleading because the server's apparent scope is a single domain lookup.
The named domain is represented by one generic consultar operation, with no explicit listing, filtering, or related process/document operations. For a simple citizen-available lookup this may be functional, but the surface is shallow and offers little workflow depth.