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 indicate idempotentHint=true and destructiveHint=false. The description adds behavioral context: it details the two authentication workflows (config vs session token) and the behavior of calling with no args to obtain a link. This adds value beyond the annotations, though it could mention error handling or token validation.
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 front-loaded with purpose and audience, then explains two usage methods. Every sentence adds value, though it could be slightly more concise. It is well-structured for an agent to parse.
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?
While the description covers the main workflows, it does not specify the return value when a token is passed (likely a success response) or error cases. Given the lack of output schema, more detail on return format and potential errors would improve completeness. However, the annotations provide safety guarantees.
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 description coverage is 0%, but the description compensates by explaining the 'token' parameter: it is a JWT to be pasted for session login. It also describes the effect of omitting the parameter (returns link). This provides meaningful semantics 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: to authenticate the user. It specifies the verb 'authenticate' and identifies the resource (MCP.AI IDE agent login). It distinguishes from sibling tools by focusing on authentication for IDE agents, which is unique among the listed siblings.
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 guidance on when to use the tool: for login via browser token, either permanently by setting config or session-only by passing the token. It also explains the alternative of calling with no arguments to get the link. While it doesn't explicitly state when not to use it, the context is well-defined.
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.
Most tools are clearly distinct, especially within the openfinance_* group, with detailed descriptions covering specific resources and actions. Minor overlap exists between list_transactions and list_transactions_by_item, and between get_credit_card_bill and list_credit_card_bills, but the descriptions clearly delineate their use cases (per-account vs whole-connection, detail vs summary).
The openfinance_* tools consistently follow a verb_noun pattern (e.g., list_accounts, get_item_status, update_transaction_category), with the exception of openfinance_provider_status which uses a noun phrase. Non-openfinance tools like authenticate, connect, marketplace, and report_bug are less uniform but still readable. Overall, the convention is mostly consistent.
At 25 tools, this is on the higher end but justified by the comprehensive Open Finance domain covering accounts, transactions, credit cards, loans, investments, connections, categories, and provider status. Each tool serves a specific operation, and the marketplace and platform utilities round out the surface. It's slightly heavy but not excessive.
The tool surface covers the full lifecycle for Open Finance data: listing and detailing accounts, retrieving balances, managing transactions (including categorization), handling credit card bills (list and detail with transactions), loans, investments, and connection health (sync, status, disconnect, search). Also includes authentication, marketplace, and utility tools. No obvious gaps for the stated purpose.