create_cost_centerCria um centro de custo novo (não-padrão — isDefault sempre começa false).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Nome do centro de custo | |
| description | No | Descrição livre do centro de custo |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| name | No | ||
| userId | No | ||
| createdAt | No | ||
| isDefault | No | ||
| updatedAt | No | ||
| description | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / name / descriptionAdded value: +"Nome do centro de custo"Input schema / properties / colorRemoved value: -{
- "type": "string"
-}Input schema / properties / descriptionAdded value: +{
+ "description": "Descrição livre do centro de custo",
+ "type": "string"
+}Input schema / properties / iconRemoved value: -{
- "type": "string"
-}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal that this is a mutating, non-idempotent, non-destructive operation. The description adds meaningful behavioral context beyond those annotations by guaranteeing that a newly created cost center always has `isDefault` set to false, which an agent could not infer from the schema alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence that states the action, the object, and the most important behavioral nuance with no wasted words. The key behavior is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple creation tool with only two parameters, one required, full schema descriptions, and an output schema present. The description plus annotations and schema cover all essential information an agent needs to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and both `name` and `description` are already described in the schema. The description does not add further parameter-level semantics, but it does not need to because the schema already carries the burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Cria') and resource ('centro de custo novo'), and adds the key distinguishing trait that created cost centers are non-default with `isDefault` starting false. This clearly separates it from update, delete, and list siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The use case is implied by the verb and the word 'novo': create a new cost center rather than updating or deleting an existing one. However, the description does not explicitly state when to prefer this over update_cost_center or mention any prerequisites, so guidance remains implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are individually well-described and many cross-reference their closest neighbors, but the set contains several easily confused clusters: create_transaction/confirm_new_transaction, update_equity/add_equity_valuation, the invoice tools (current_invoice, next_invoice, list_pending_invoices, get_invoice), and the many analytics/projection tools. The descriptions help a careful reader, but with 81 tools an agent is likely to misselect among these overlapping surfaces.
CRUD operations consistently use create_/list_/update_/delete_ plus a resource noun, and all names are snake_case. However, there is a large second group of noun-phrase analytics tools (cashflow_forecast, spending_projection, categories_insights, transport_routine) plus one-off verbs such as can_afford, pay_invoice, and validate_current_invoices, so the naming convention is mixed even though it remains readable.
81 tools is far beyond the practical MCP tool surface and exceeds the rubric's 50+ extreme-mismatch threshold. Even if each tool maps to a real finance endpoint, the volume overwhelms an agent's context window and makes selection much harder.
The server covers the finance lifecycle extensively: accounts, cards, invoices, transactions, recurring rules, budgets, goals, debts, equities, categories, tags, cost centers, profile, projections, and insights all have working read/write paths. Minor gaps remain, such as no update/delete for tags and no direct update/delete for system-generated invoices, but agents can usually work around these.