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. The description explains that calling without args returns a link, and calling with token sets it. It does not contradict annotations and adds context about the login flow, though it does not mention error handling or multiple calls.
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 slightly verbose; it could be more concise by separating the two methods more cleanly. However, it is well-structured and serves its purpose without filler.
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 has one optional parameter and no output schema, the description covers all necessary aspects: what the tool does, how to use it in two scenarios, and what the token is. It is complete for the tool's complexity.
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% coverage for parameter descriptions, but the description fully explains the 'token' parameter: it is a JWT from browser login, and how to use it for session or permanent login. This significantly adds 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 is for authentication, specifying that it returns a login link or accepts a token for session login. It distinguishes itself from sibling tools, which are unrelated to authentication.
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 two clear usage methods: permanent configuration via config header or session login by pasting a token. It also mentions calling with no args to get the link. However, it does not explicitly state when not to use the tool or name specific alternatives.
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 tools are largely distinct, especially the openfinance_* suite which follows clear resource+action patterns. A few could be confused (e.g., openfinance_list_transactions vs openfinance_list_transactions_by_item, or get_account_balance vs list_accounts) but descriptions are thorough and clarify boundaries. The non-prefixed tools (authenticate, connect, marketplace) are also distinct, though 'marketplace' is quite overloaded internally.
The openfinance_* tools follow a very consistent verb_noun pattern (list, get, force_sync, update, search, provider_status). However, the platform tools are heterogeneous: authenticate, connect, report_bug, show_version are verb_noun, but 'marketplace' and 'toolkit_info' are nouns. This mix is a minor inconsistency, but overall the naming is predictable across the two clear groups.
At 25 tools, this is on the heavy side (16-25 is considered heavy), but the breadth is justified by a comprehensive Open Finance API (19 tools) plus platform management (6 tools). Each openfinance_* tool maps to a specific endpoint or operation, so none feel redundant. Slightly above the ideal 3-15 range, but appropriate for a full financial data adapter.
The Open Finance surface is remarkably complete: accounts, transactions, bills, loans, investments, categories, connection management (list, force_sync, status, provider_status, search connectors, disconnect), and even a categorization update. The platform side covers authentication, connectivity, marketplace operations (search/describe/invoke/install/subscribe), bug reporting, version, and toolkit info. No obvious dead ends or missing lifecycle steps.