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PicPay MCP

by io.github.mcp-dir

openfinance_update_transaction_category

Corrects the category of one or more transactions (PATCH /transactions/:id). Pass items as an array of { transaction_id, category_id } — transaction_id comes from openfinance_list_transactions, category_id from openfinance_list_categories. This overrides Pluggy's automatic categorization AND teaches Pluggy: recategorizing a transaction automatically creates a Category Rule for this client (case-insensitive exact match on the transaction's data), so FUTURE similar transactions are categorized the same way — use this to fix miscategorized transactions and improve categorization accuracy going forward. Batch shape: returns { updated, results: [{ transaction_id, category, categoryId }], errors: [{ id, status, message }] } — per-item errors do not fail the whole batch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes

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
  6. Removed
  7. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint=false, destructiveHint=false), the description discloses that the tool overrides automatic categorization and teaches Pluggy by creating a Category Rule. It also details the batch response shape with per-item error handling, providing full behavioral transparency.

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 is front-loaded with purpose and covers parameter format, side effects, and response shape. It is efficient but could be slightly more concise; every sentence contributes value.

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, the description explicitly describes the batch response structure (`{ updated, results, errors }`) and explains partial error handling. It covers all necessary context for correct usage, including side effects and data sources.

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?

With 0% schema description coverage, the description fully compensates by explaining that `items` is an array of { transaction_id, category_id } and specifies the source of each ID (from list_transactions and list_categories). This adds critical meaning beyond the bare schema.

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 the tool's purpose: 'Corrects the category of one or more transactions'. It uses a specific verb ('corrects') and resource ('transactions'), and distinguishes itself from sibling tools like openfinance_list_transactions and openfinance_list_categories by specifying the update action.

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 clear context on when to use the tool: to fix miscategorized transactions and improve future categorization. It tells where to obtain required IDs (from list_transactions and list_categories) and explains the side effect of creating a Category Rule. However, it does not explicitly state when not to use the tool, leading to a score of 4.

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
Disambiguation4/5

Most tools have clearly distinct purposes, especially within the openfinance_* family where each targets a different resource or action. A few minor overlaps exist—connect vs toolkit_info both report connection state, and marketplace internally includes report_bug while a top-level report_bug also exists—but these are unlikely to cause serious misselection.

Naming Consistency4/5

The openfinance_* tools follow a consistent snake_case prefix with mostly verb_noun patterns like list_accounts, get_item_status, and force_sync. The general tools are also snake_case but mix verbs (connect, authenticate) with nouns (marketplace, toolkit_info), and openfinance_provider_status breaks the verb_noun pattern slightly.

Tool Count3/5

25 tools is at the upper boundary of a heavy surface, but the Open Finance domain genuinely spans connections, accounts, transactions, bills, loans, investments, categories, and provider health. It feels dense rather than bloated, though a few general utilities like show_version and report_bug could arguably be consolidated.

Completeness4/5

The Open Finance surface is well covered: connection management, account/balance/transaction retrieval, credit card bills, loans, investments, category correction, force sync, and provider status are all present. Minor gaps exist—such as no direct investment position detail endpoint beyond the portfolio list, and payments/initiation are out of scope—but agents can accomplish the core read-only financial workflows without dead ends.

Resources