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 does not contradict annotations. It transparently explains that calling without token returns a login link, and calling with token performs session authentication. No destructive or read-only behavior is implied beyond what annotations state.
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?
Three sentences, each serving a clear purpose. Could be slightly more concise, but the structure is logical and front-loaded with the main 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?
For a simple authentication tool with one parameter and no output schema, the description covers the essential workflow. It lacks explicit return format but is sufficient for an agent to understand invocation.
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 for the 'token' parameter, but the description compensates fully by explaining it is a JWT and how to use it in both modes.
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 is for authentication, distinguishing the two use cases (permanent config vs session-only login) with specific instructions. The verb 'authenticate' is implicit but well-defined, and it is unique among 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 explicitly explains when to use each mode: for permanent access add to config, for session-only paste token. It provides instructions for calling with or without arguments, making it easy for the agent to decide.
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 resource and action: balances, transactions, bills, loans, investments, connections, categories, and system functions. While some tools are related (e.g., list_transactions vs list_transactions_by_item), their purposes are clearly separated by granularity and intent, with no true overlap.
The Open Finance tools follow a strict 'openfinance_verb_noun' pattern (e.g., list_accounts, get_balance, update_transaction_category), and the broader system tools use clear verb-based names. All use snake_case consistently with no mixing of conventions.
At 25 tools, this is on the higher end of the range, but the breadth is justified by the Open Finance domain: accounts, transactions, bills, loans, investments, connections, plus marketplace and system operations. Each tool adds unique value, though the count is slightly heavy.
The server covers the core Open Finance lifecycle: connection management, account/transaction/bill/loan/investment retrieval, category correction, and provider status. Minor gaps like a dedicated 'get single investment' tool are covered by list_investments plus list_investment_transactions. Overall, no dead ends for data access.