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 idempotent and non-destructive. The description adds valuable behavioral context: token-based session login vs. permanent header config, non-expiring vs. session-only, and the no-args behavior. No contradiction with 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 a single, information-dense paragraph covering all usage modes. It is somewhat verbose and has a minor grammar redundancy ('log in in'), but every sentence serves a purpose.
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 simple schema (one optional param) and no output schema, the description covers the full authentication workflow: browser login, token retrieval, config option, session option, and no-arg invocation. It is complete for an agent to use 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 0% description coverage, but the description fully explains the 'token' parameter as a JWT to paste for session login, and clarifies that omitting it returns a login link. This compensates completely for the bare schema.
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's purpose: logging in via browser and providing an access token. It identifies the specific resource ('MCP.AI for IDE agents') and the authentication action, distinguishing it from sibling tools like connect or marketplace.
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?
Explicit conditional guidance is given: the preferred permanent config approach vs. a session-only paste, and the no-args case for generating a login link. This tells the agent exactly when and how to invoke the tool.
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 core consultation tool is distinct, but authenticate and connect overlap somewhat around authentication/connection status, and marketplace is a sprawling tool covering many sub-actions (search, invoke, install, etc.) that overlaps with report_bug and toolkit_info. Detailed descriptions help, but boundaries remain fuzzy.
Tool names mix single-word verbs (authenticate, connect), noun_verb (report_bug, show_version), noun_noun (toolkit_info), a marketplace noun, and a Portuguese domain name (similaridade_br_consultar). There is no consistent naming convention across the set.
Seven tools is a reasonable size, but most tools are generic MCP platform utilities rather than serving the identity similarity purpose. The count itself is fine, though the scope feels a bit unfocused.
The primary operation of querying identity similarity is covered, along with authentication and connection status. Billing and marketplace operations are also present. Minor gaps exist, such as no explicit balance/credit check, but these are indirectly handled via marketplace links.