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 declare idempotentHint=true and destructiveHint=false, so the safety profile is clear. The description adds that the token is a JWT and that session login expires, but it doesn't disclose what the tool returns or the exact behavior when called with no args vs with a token. It partially compensates but lacks some behavioral detail (e.g., does it validate the token, what is the output). No contradiction.
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?
Two sentences, front-loaded with the audience and purpose. Each clause adds value, and the formatting guides the agent on parameter usage. Zero waste.
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's complexity (auth flow) and the minimal schema, the description covers the two usage modes, the token format, and the alternative permanent config. The sibling list shows no overlap, so no additional context is needed. Complete for an agent to invoke 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?
Schema coverage is 0% since the description explains the token parameter's format (JWT) and its optionality, but the schema provides no description. The description adds meaning beyond the schema by detailing the two call patterns, which is helpful. It earns a solid 3 because it compensates for the schema deficit.
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 authenticates an IDE agent by logging in via browser and obtaining an access token. It distinguishes itself from siblings by explicitly targeting IDE agents and explaining the two login flows (permanent config vs session-only).
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 when-to-use guidance: it tells the agent to guide the user to log in, offers two methods (config header permanent, or paste token session), and specifies calling with no args to get the link. It also mentions sibling tools like report_bug and show_version are unrelated to auth workflows.
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 targets a distinct function: CEP lookup, quote validation, dashboard stats, account listing, business listing, insurer listing, and separate platform utilities for auth, connectivity, marketplace, bug reports, version, and toolkit state. No two tools overlap in purpose, so an agent can clearly differentiate them.
Tool names mix conventions: some are bare nouns (agger_cep, agger_negocios, marketplace), some use verb_noun (agger_list_accounts, report_bug, show_version), one is noun_verb (agger_cotacao_validar), and several are generic single verbs (authenticate, connect). This inconsistency makes the naming pattern unpredictable and harder to infer.
The 12-tool set is well-scoped: 6 domain-specific Agger tools cover the core insurance broker workflows, and 6 generic platform tools handle authentication, connectivity, marketplace operations, and diagnostics. Each tool earns its place without unnecessary bloat.
The domain coverage is partial: the server supports listing businesses, validating quotes, and viewing insurers, but lacks create/update/delete operations for quotes or detailed single-item views. Some gaps exist (e.g., no create quote, no get_business_detail), but agents can work around them by using the list and validation tools, and the platform utilities address meta-level needs.