Skip to main content
Glama

Monte Bravo 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 recategorizing creates a Category Rule for future similar transactions, explains batch error handling (per-item errors do not fail the whole batch), and specifies the return shape. This adds significant value.

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 slightly verbose but front-loaded with the main action. Every sentence adds value, covering side effects, batch behavior, and error handling. A minor trim could improve conciseness.

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 the complexity (side effect, batch processing, error handling) and lack of output schema, the description is complete. It explains the return shape, error list, and the learning mechanism, leaving no critical gaps.

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?

Schema coverage is 0%, but the description fully explains the 'items' parameter as an array of { transaction_id, category_id }, and tells where to get these IDs (from openfinance_list_transactions and openfinance_list_categories). This compensates for the lack of schema descriptions.

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 states 'Corrects the category of one or more transactions (PATCH /transactions/:id)', which uses a specific verb and resource. It clearly distinguishes from sibling tools like openfinance_list_transactions and openfinance_list_categories.

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 explicitly says 'use this to fix miscategorized transactions and improve categorization accuracy going forward', providing clear when-to-use guidance. It does not explicitly state when not to use or name alternative tools, but the context is clear.

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

All Monte Bravo MCP toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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