Lists loan contracts per bank connection (GET /loans). Pass items as an array of connection selectors (item_id uuid, connector_id, or connector_name) — one entry per connection to fetch; multiple connections are queried sequentially with rate-limit spacing. OMIT items to list loans across ALL linked banks. Returns { results, errors } per connection.
| Name | Required | Description | Default |
|---|---|---|---|
| items | 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 already indicate read-only and idempotent. The description adds the sequential query behavior, rate-limit handling, and the return structure per connection, which goes beyond annotations.
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 dense sentences with no wasted words. The key details are front-loaded.
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 includes the return shape (`{ results, errors }` per connection). It covers input variation and behavior, though some detail on results fields is missing, but acceptable for a list 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?
With 0% schema coverage, the description fully explains the `items` parameter meaning (connection selectors) and its omission behavior. This is critical for correct usage.
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 explicitly states it lists loan contracts per bank connection and specifies the endpoint. It distinguishes from siblings like openfinance_get_loan_detail by focusing on listing across connections.
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?
It clearly explains when to include or omit the `items` parameter and mentions sequential querying with rate-limit spacing. It does not explicitly exclude alternative tools but provides sufficient context.
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 have clearly distinct purposes within the openfinance_* namespace, but some close pairs exist: get_account_balance vs get_accounts_detail, list_transactions vs list_transactions_by_item, and get_item_status vs provider_status vs force_sync all require careful reading. The detailed descriptions resolve most ambiguity, but selection is not always instant.
The openfinance_* tools follow a consistent snake_case verb_noun pattern (list_accounts, get_account_balance, update_transaction_category, force_sync). However, the generic platform tools like authenticate, connect, marketplace, and toolkit_info break the pattern, and provider_status is a noun phrase rather than verb_noun.
At exactly 25 tools, this sits at the heavy boundary. The Open Finance domain justifies many of them, but the set feels bloated because marketplace alone bundles a large number of sub-operations, and several platform utilities could arguably be consolidated.
The Open Finance surface is quite complete: connections, accounts, balances, transactions, credit card bills, investments, loans, categories, sync, status, and provider health are all covered. Minor gaps exist around direct connection creation (delegated to URLs) and single-item transaction detail, but agents can work around them.