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 indicate read-only, non-destructive, idempotent. Description adds sequential query behavior and return format, providing valuable context 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 sentences, front-loaded purpose, no wasted words.
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?
With no output schema, description includes return format. Covers all key behaviors for this one-parameter 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?
Schema has 0% coverage, but description fully explains 'items' as connection selectors with types and usage, compensating completely.
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?
Clearly states 'lists loan contracts per bank connection' with specific verb and resource. Distinguishes from siblings like openfinance_get_loan_detail.
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?
Explains when to use 'items' parameter and when to omit for all banks. Mentions sequential queries and rate limiting. Could explicitly mention 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.
Most openfinance_* tools target distinct resource/action pairs, but openfinance_list_connections and openfinance_get_item_status overlap on connection status/reconnect URLs, and openfinance_list_transactions vs openfinance_list_transactions_by_item can be confused. The long descriptions reduce ambiguity, but selection risk remains.
The openfinance_* block is consistently verb_noun, but the platform tools mix bare verbs (authenticate, connect), nouns (marketplace), and noun_info (toolkit_info). No single naming convention spans the whole set, though each subgroup is internally readable.
At 25 tools, this sits at the top of the heavy borderline range. The broad scope—MCP.AI platform management, prompt library, and Open Finance data—justifies many tools, but the set feels like a bundled suite rather than a tightly scoped single-purpose server.
The Open Finance side is well covered: accounts, balances, transactions, credit card bills, loans, investments, connections, sync, status, provider health, and category updates. The platform side has auth, toolkit info, marketplace, and feedback. Minor gaps exist, such as no explicit identity fetch or payment initiation, but those seem outside the intended read/analysis domain.