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 provide readOnlyHint=false, destructiveHint=false, idempotentHint=true. The description adds context about login flow, token usage, and permanent vs session behavior, which goes beyond annotations without contradiction.
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 slightly long but well-structured, with a clear first sentence and detailed explanation of usage. Every sentence adds value, though it could be more succinct.
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 no output schema, the description covers the authentication flow, method selection, and token handling. It could mention error cases or token format, but is fairly complete for an auth tool.
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 one optional parameter 'token' with 0% coverage. The description fully explains its purpose: either provide a JWT for session login or omit to get a link. This adds crucial meaning beyond 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 states it is for authentication, explaining two methods: browser login to get a permanent token via config, or session-only by pasting a token. It distinguishes from siblings like 'connect' by focusing on authentication flow.
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 clearly explains when to use each method: for permanent connection via config, or for session login by pasting token, or with no args to get a link. It lacks explicit when-not-to-use or alternatives among siblings but provides clear situational 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.
The openfinance_* tools are clearly separated by resource and action, and their detailed descriptions make most choices unambiguous. However, marketplace is a multi-action mega-tool that duplicates report_bug, and openfinance_list_transactions vs openfinance_list_transactions_by_item have some overlap that could cause misselection.
The 19 openfinance_* tools follow a consistent and predictable 'openfinance_<verb>_<noun>' pattern. The non-openfinance tools are a mixed set (marketplace, toolkit_info, show_version, report_bug, authenticate, connect), which is readable but not fully uniform.
25 tools lands right at the heavy end of the borderline range. The Open Finance domain genuinely has many distinct resources, but the marketplace tool alone packs in many sub-actions, which makes the total tool count feel more bloated than the domain strictly requires.
The surface covers the full Open Finance lifecycle well: connections, sync/disconnect, accounts, transactions, credit card bills, loans, investments, categories, provider health, and platform administration. Minor gaps exist, such as no direct connect/add-bank tool beyond returning a connect_url and no get-single-transaction endpoint, but agents can work around these.