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 behavioral traits beyond annotations: it explains the two authentication modes (permanent config vs session-only token), and that calling with no args returns a link. Annotations already indicate idempotent and non-destructive, and the description adds useful context about token expiry and session lifetime, though it doesn't detail error cases or response format.
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 two sentences and about 70 words, which is appropriately sized for the information it conveys. It is front-loaded with the purpose ('MCP.AI for IDE agents'), though the second sentence is a bit run-on and could be broken into clearer steps. Still, every sentence earns its place and there is no 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?
Given this is a simple auth tool with only one optional parameter and no output schema, the description is quite complete: it covers the auth flow, the two modes, and even alternative configuration. It could be slightly more explicit about what the tool returns after a token is provided, but overall it gives sufficient context for an agent to invoke it 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 only parameter `token` has 0% schema description coverage, but the description fully compensates. It explains that `token` is a JWT to be pasted for session-only login, and that omitting it triggers the link retrieval. This adds complete semantic meaning beyond the raw 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: authenticating IDE agents to MCP.AI via a browser login and access token. It identifies the resource (MCP.AI) and the action (log in / authenticate), and it stands apart from sibling tools which are mostly finance-related.
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 gives explicit when-to-use guidance: it recommends the permanent config-based header approach as the best practice, and describes the session-only token paste alternative. It also instructs when to call with no args (to get the link) vs with a token, which is effectively usage guidance.
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 distinct, with clear descriptions differentiating them. Some overlap between openfinance_list_accounts and openfinance_get_accounts_detail, but descriptions clarify that one returns summaries and the other full details. The marketplace tool is very detailed and avoids confusion with Open Finance tools.
The Open Finance tools follow a consistent openfinance_verb_noun pattern, but other tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) do not use a prefix. This mix of conventions reduces overall consistency, though within the Open Finance subset the pattern is clear.
24 tools is a reasonable count for a platform covering authentication, marketplace, and detailed Open Finance operations. The number is slightly high but each tool has a clear purpose and none seem redundant.
The tool set covers the full lifecycle of bank connections: listing accounts, transactions, credit card bills, investments, loans, force syncing, provider status, and category management. The marketplace tool also allows extending functionality. No obvious gaps for the intended financial data domain.