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odoo19-mcp-server

odoo19-mcp-server

by twtrubiks

Get Fields

get_fields
Read-onlyIdempotent

Retrieve field definitions and attributes for any Odoo model. Provide a model name to get all fields, or specify field names and attributes to narrow results.

Instructions

Get field information for an Odoo model using ORM fields_get().

Input Schema

NameRequiredDescriptionDefault
modelYesModel name (e.g., 'res.partner')
fieldsNoSpecific field names to retrieve (None = all fields)
attributesNoField attributes to return (None = default attributes including type, string, help, required, readonly, store, selection, comodel_name, inverse_name, domain)
field_filterNoOptional filter for field name (e.g., 'name' to find name-related fields)

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / properties / attributes / description
      Added value: +"Field attributes to return (None = default attributes including\n       type, string, help, required, readonly, store, selection,\n       comodel_name, inverse_name, domain)"
    • addedInput schema / properties / field_filter / description
      Added value: +"Optional filter for field name (e.g., 'name' to find name-related fields)"
    • addedInput schema / properties / fields / description
      Added value: +"Specific field names to retrieve (None = all fields)"
    • addedInput schema / properties / model / description
      Added value: +"Model name (e.g., 'res.partner')"
  2. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds no behavioral context beyond the ORM method name – nothing about metadata vs data, cost, or what happens with an unknown model. With annotations doing the heavy lifting it is not misleading, but it adds little.

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?

A single front-loaded sentence with no filler. The trailing ORM implementation reference is arguably the least useful part but is not wasteful enough to penalize heavily.

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

Completeness3/5

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

An output schema exists, so return values need not be explained. For a simple read-only metadata tool the description is minimally adequate, but it omits any guidance on filtering versus returning all fields – a distinction the description could clarify beyond the schema defaults.

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

Parameters3/5

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

Schema description coverage is 100% with 4 well-documented params (model, fields, attributes, field_filter), so the schema already carries full parameter meaning. The description contributes nothing additional about parameters, making the baseline 3 correct.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (get) and resource (field information for an Odoo model), and names the underlying ORM call (fields_get()). An agent can tell it retrieves schema/metadata rather than record data. It does not explicitly contrast with list_models, so it stops short of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus list_models, read_records, or execute_method. No prerequisites, no when-not conditions, no mention of alternatives. Usage is left entirely to inference.

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