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Odoo MCP Connector for ChatGPT and Claude

by com.speaktoyourdatabase
OverviewDiscussionsAdmin

List workspaces

list_workspaces
Read-onlyIdempotent

Use this when the user asks which STYD workspaces (companies) they can use, their role in each, or how many prompts are left. Signed in with a STYD account: every workspace the user belongs to, each a separate company's data. With an API key: the key's one workspace. Each record has the workspace name, its workspace_id, the user's role there and the prompts left; records are ordered by workspace_id, lowest first. Not needed before asking a question: list_connections and every answer name the workspace. Uses no prompt.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_workspaces"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and closed-world, so the safety profile is covered. The description adds genuinely new behavior: auth-dependent scope (all workspaces for an account vs. one workspace for an API key), ascending workspace_id ordering, and 'uses no prompt' cost disclosure. These are real operational facts not present in the annotations.

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?

Front-loaded with the trigger and scoped tightly; nearly every clause carries information (auth scope, fields, ordering, cost). The one wrinkle is 'Not needed before asking a question: list_connections and every answer name the workspace,' whose colon construction is slightly awkward to parse on first read.

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?

With no output schema, the description carries the return-value burden and does: it lists every field per record and the ordering. Combined with the auth-mode scoping and cost note, an agent has everything needed to call and interpret this zero-parameter tool.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate at the input level. It instead spends the space on output semantics, which is the appropriate use here.

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?

States a specific verb+resource ('list workspaces (companies)') and enumerates what each record contains (name, workspace_id, role, prompts left). It also distinguishes the two auth modes' scopes, so an agent knows exactly what set is returned without opening a schema.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('when the user asks which STYD workspaces they can use, their role in each, or how many prompts are left') and an explicit non-use case ('Not needed before asking a question: list_connections and every answer name the workspace'), naming the sibling tool that covers it.

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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