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Uber Conta by Digio 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

TDQS

A4.8/5.0
Behavior5/5

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

The description thoroughly discloses critical behavioral traits beyond annotations: it overrides Pluggy's automatic categorization and teaches Pluggy by creating a Category Rule that affects future transactions. It also explains batch behavior including per-item error isolation. Annotations provide no such detail, making this description the primary source of transparency.

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

Conciseness5/5

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

The description is front-loaded with the tool's purpose and uses efficient, dense language. Every sentence adds critical information: operation, parameter format, side effects, batch response shape, and per-item errors. Though lengthy, it is well-structured and avoids redundancy.

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?

The description is complete for the tool's complexity: it covers the operation, parameter construction, side effects (rule creation), batch response shape, and error handling. Since no output schema exists, the description compensates by detailing the return structure. No critical gaps remain for an agent to invoke the tool correctly.

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?

Despite zero schema description coverage, the description fully explains the `items` parameter structure, the required fields (transaction_id and category_id), and provenance of each ID. This goes far beyond what the minimal schema provides, making parameter semantics exceptionally clear.

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 function with a specific verb ('Corrects the category'), identifies the HTTP method (PATCH /transactions/:id), and differentiates it from sibling tools like openfinance_list_transactions and openfinance_list_categories by focusing on modification rather than retrieval.

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 usage context, specifying that the tool is for fixing miscategorized transactions and improving future categorization. It also explains where input parameters come from (openfinance_list_transactions and openfinance_list_categories). However, it does not explicitly mention alternatives or when not to use the tool, so it falls short of a 5.

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

A4.3/5.0
Disambiguation4/5

The openfinance_* tools are mostly distinct list/get/update/sync operations, and the non-openfinance tools are clearly separate platform utilities. A few pairs could be confused, such as openfinance_list_accounts vs openfinance_get_accounts_detail, or openfinance_get_item_status vs openfinance_list_connections, but the descriptions generally make the intended use clear.

Naming Consistency4/5

The domain tools follow a consistent openfinance_verb_noun pattern, making the bulk of the API predictable. The deviation comes from the six non-prefixed platform tools, and one or two names like openfinance_provider_status are noun-led rather than verb-led, but overall the convention is coherent.

Tool Count3/5

25 tools is at the heavy end of the range, and the server would feel tighter if some get/list pairs were consolidated. However, the breadth is somewhat justified by the number of Open Finance resource types covered: accounts, transactions, bills, investments, loans, connections, categories, and sync/status operations plus platform utilities.

Completeness5/5

The Open Finance surface is thorough: connection lifecycle, account data, balances, transactions, credit card bills, investments, loans, categories, sync, and provider health are all covered. There are no significant dead ends, and the additional platform tools handle authentication, marketplace discovery, and system information.

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