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Monte Bravo MCP

by io.github.mcp-dir

openfinance_get_loan_detail

Read-onlyIdempotent

Returns full loan contract detail by id (GET /loans/:loanId): interestRates[] (taxType, ratePercentage, indexer), contractedFinanceCharges[], balloonPayments[], warranties[], installments schedule (installmentsCount, paidInstallments, numberOfInstallmentsRemaining, installmentFrequency), amortizationScheduled, CET, ipocCode and dates. Use after openfinance_list_loans to deep-dive on a specific contract. Pass loan_ids as an array (1-50). { results, errors } batch shape.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
loan_idsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. Added

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds value by detailing the batch response shape ({ results, errors }) and the parameter constraint (array of 1-50). No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that fronts the core purpose and then adds details; while thorough, it could be slightly more concise (e.g., reducing field listing). However, every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and only one parameter, the description provides sufficient completeness: it enumerates key fields, specifies parameter constraints, explains the batch response format, and includes a usage workflow reference. No gaps that would hinder an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage; the description fully compensates by specifying that loan_ids is an array of strings limited to 1-50 items, and explains the expected batch response shape, adding crucial context for correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns full loan contract detail by ID, enumerating specific fields (interestRates, amortizationScheduled, etc.), and distinguishes from the sibling openfinance_list_loans by indicating this is a deep-dive tool for specific contracts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises to use after openfinance_list_loans, providing a clear workflow. Specifies the batch shape and array size limit (1-50), but does not mention when not to use or alternative tools for other data.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation3/5

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.

Naming Consistency3/5

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.

Tool Count3/5

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.

Completeness4/5

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.

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