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 declare idempotent and non-destructive hints, but the description adds valuable context about session vs. permanent login, the token format, and the behavior of calling with no arguments (returning a link). It does not contradict 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 informative but somewhat rambling with parentheses and semicolons. However, it is front-loaded with the key purpose and each sentence delivers useful guidance, so it is still concise for the amount of information provided.
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 simplicity (one optional parameter, no output schema), the description covers all necessary aspects: the configuration alternative, session token usage, and no-args behavior. It is complete for an agent to select and invoke the tool 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?
The schema has only an optional 'token' property with no description (0% schema coverage). The description compensates fully by explaining that the token is a JWT to be passed for session-only login, and that omitting it triggers a link retrieval. This is comprehensive.
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 explicitly states the authentication workflow: log in through the browser, copy the access token, and either add it to the server config or pass it as a parameter. It clearly differentiates this from sibling tools by focusing on the authenticate action and its two modes.
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 clear context for when to use this tool, including the 'Best' option for permanent config-based authentication and the alternative session-only token passing. It also notes the no-args behavior to get a link, but it does not explicitly compare to the sibling 'connect' tool or state exclusions.
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 are mostly distinguishable: the domain query is unique, and platform tools like authenticate, connect, and report_bug have clear roles. However, connect and toolkit_info both report connection status, and marketplace handles a wide range of actions, causing minor overlap.
Names mix verbs (authenticate, connect), nouns (marketplace), and underscores with inconsistent ordering (report_bug vs toolkit_info vs situacao_eleitoral_consultar). There is no uniform verb_noun pattern across the set.
Seven tools is a reasonable count for a platform wrapper with one domain integration. Each tool serves a purpose, though show_version is trivial and marketplace is oversized.
The domain surface is minimal—only a single consult operation for electoral status, which is appropriate for a read-only public query. The platform tools extend capability via the marketplace, but for a dedicated TSE server, additional operations like batch or status checks are missing.