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Glama

Monte Bravo MCP

by io.github.mcp-dir

openfinance_list_investments

Read-onlyIdempotent

Returns the investment portfolio for a connection (broker or bank with INVESTMENTS product enabled): FIIs, stocks, ETFs, fixed income (CDB/LCI/LCA/Tesouro), mutual funds, retirement (previdência) and COE. Each row carries balance, amount, amountOriginal, amountProfit, lastMonthRate / annualRate / lastTwelveMonthsRate (when available), dueDate, issuer, ISIN, etc. Returns { total:0, results:[], warning } instead of throwing when INVESTMENTS isn't enabled (403) or other upstream errors. DATA INTEGRITY: when MULTIPLE positions come back as TOTAL_WITHDRAWAL with balance/quantity 0 at once (mass zeroing), the tool cross-checks each position's own transaction history upstream; if the zeroing is contradicted (BUY with no sale/redemption/transfer) the response carries data_integrity_warning and the affected rows are flagged integrity:'suspect_zeroed' — treat those balances as UNAVAILABLE (likely a temporary connector failure publishing zeros), never as real R$0, and do NOT sum them into the portfolio.

Bulk support: accepts item_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemNo
pageNo
typeNo
item_idNo
item_idsNo
page_sizeNo

Schema Changelog

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

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. Changed2 schema fields changed
    • addedInput schema / properties / item_id
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / item_ids
      Added value: +{
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  6. Added
  7. Removed
  8. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds significant behavioral context: error handling (returns structure instead of throwing), data integrity checks via transaction history cross-referencing, and specific warnings. No contradiction with annotations.

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 detailed but well-structured with paragraphs for different aspects (purpose, error handling, data integrity). It is front-loaded with the main purpose. While somewhat lengthy, all sentences add value, so it's acceptable.

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

Completeness4/5

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

Given 6 parameters and no output schema, the description covers output behavior thoroughly, including error handling and data integrity. However, it lacks parameter explanations, which is a gap. Overall, it provides enough context for an agent to use the tool correctly in most scenarios.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It only explains item_ids for bulk execution but does not clarify parameters like item, page, type, or page_size. This leaves the agent guessing about their meaning and usage.

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 explicitly states it returns investment portfolio data for a connection, listing specific asset types like FIIs, stocks, ETFs, etc., and details the fields included. This clearly distinguishes it from sibling tools such as openfinance_get_account_balance or openfinance_list_accounts.

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?

The description provides guidance on bulk execution via item_ids and explains behavior when INVESTMENTS is not enabled. It also discusses data integrity warnings, telling the agent not to sum suspect_zeroed rows. However, it does not explicitly state when to avoid using this tool or compare directly with alternatives.

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.

Resources