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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true and no destructive effects. The description adds value by explaining that calling with no args returns a login link, and with a token it processes the JWT. It also explains the difference between permanent and session tokens, which is beyond what annotations provide.
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 front-loads the purpose and provides structured steps, but could be more concise without losing clarity. Some repetition exists (e.g., 'log in in the browser').
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 optional parameter and no output schema, the description provides sufficient context: what it does, how to use it in two scenarios, and the expected behavior. It covers the key aspects an agent needs to invoke 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 input schema has one parameter 'token' with 0% description coverage. The description compensates by explaining how to use the token parameter: 'call with { token: '<jwt>' }' for session login, and clarifies its role. This adds essential meaning.
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: authentication for MCP.AI IDE agents. It explains two distinct methods (config token for permanent connection, session token via parameter). It distinguishes itself from sibling tools like 'connect' by focusing specifically on 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 explicit when-to-use guidance: for logging in. It offers a best practice (adding token to config) and an alternative (pasting token as a session parameter). While it doesn't explicitly state when not to use, the context is clear.
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 mostly distinct, but several have overlapping boundaries: openfinance_list_transactions vs openfinance_list_transactions_by_item, openfinance_get_item_status vs openfinance_provider_status, and openfinance_list_accounts carrying balance vs openfinance_get_account_balance. The platform-level tools also blur somewhat: marketplace, toolkit_info, and connect all touch installed or available services.
The openfinance_* group follows a consistent list/get/update verb pattern in snake_case, but platform-level tools like authenticate, connect, marketplace, report_bug, show_version, and toolkit_info break that convention. The set is readable, but it is split between two clearly different naming styles.
At 25 tools, the server is at the heavy end, and several are platform/MCP-management helpers rather than core banking capabilities. The count is not absurd for a broad Open Finance + marketplace adapter, but it feels more cluttered than a focused financial data toolset should be.
The Open Finance surface is thorough: accounts, transactions, balances, credit card bills, loans, investments, connection lifecycle, sync, provider status, and category correction are all covered. The main gaps are the absence of a direct connect/create action (only URLs are returned) and no write operations beyond category updates, but for a read-centric financial data adapter this is close to complete.