odoo19-mcp-server

by twtrubiks

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

Count Records

count_records

Read-onlyIdempotent

Count records in a specified Odoo model using optional domain filters to get exact totals for reporting or validation.

Instructions

Count records in an Odoo model matching the domain.

Input Schema

Name	Required	Description	Default
`model`	Yes	Model name (e.g., 'res.partner')
`domain`	No	Odoo search domain (list of conditions). Examples: - Simple: [["active", "=", True]] - Multiple (AND): [["is_company", "=", True], ["country_id", "=", 1]] - OR condition: ["\|", ["type", "=", "contact"], ["type", "=", "invoice"]] - any (Odoo 19+): [["order_line", "any", [["product_uom_qty", ">", 5]]]] - Operators: =, !=, >, >=, <, <=, like, ilike, in, not in, child_of, any

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedApr 30, 2026

addedInput schema / properties / domain / description

Added value: +"Odoo search domain (list of conditions). Examples:\n- Simple: [[\"active\", \"=\", True]]\n- Multiple (AND): [[\"is_company\", \"=\", True], [\"country_id\", \"=\", 1]]\n- OR condition: [\"|\", [\"type\", \"=\", \"contact\"], [\"type\", \"=\", \"invoice\"]]\n- any (Odoo 19+): [[\"order_line\", \"any\", [[\"product_uom_qty\", \">\", 5]]]]\n- Operators: =, !=, >, >=, <, <=, like, ilike, in, not in, child_of, any"

addedInput schema / properties / model / description
```
Added value: +"Model name (e.g., 'res.partner')"
```

First observedv1.0.0Apr 2, 2026

TDQS

C2.9/5.0

Behavior2/5

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

Annotations already declare readOnlyHint and idempotentHint, so safety is covered. The description adds essentially nothing beyond that: it does not say what happens when domain is omitted (the null default), whether counting is bounded or expensive on large models, or how the count is returned.

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 clause with zero filler, front-loading the verb and resource. It is arguably terse to the point of under-specification, which keeps it from a 5.

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?

With an output schema present, return values need not be explained, and annotations cover the safety profile. What is missing is the default behavior when domain is null (count everything) and any cost/performance caveat, which matters for a count over arbitrary models.

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%, including extensive domain examples and the operator list, so the schema carries the full parameter burden. The description only restates that the domain filters, adding no syntax or format detail beyond the schema. Baseline 3 applies.

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 and resource ('Count records in an Odoo model') plus the filtering mechanism ('matching the domain'), so the operation is unambiguous. It does not explicitly contrast itself with search_records or read_records, which is where it loses a point.

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 instead of the many sibling read tools (search_records, read_records), nor any prerequisite or exclusion. The agent must infer that this is the cheap alternative when only a number is needed.

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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