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Odoo MCP Connector for ChatGPT and Claude

by com.speaktoyourdatabase
OverviewDiscussionsAdmin

Describe available data

describe_available_data
Read-onlyIdempotent

Use this when the user asks what they can ask, or whether something is covered (for example a specific Odoo app, or a table). Takes the connection_id of the data source (from list_connections). The result depends on the source. Odoo: business areas the user's Odoo access can read, the areas STYD does not answer yet, and example questions. PostgreSQL / MySQL: the tables the user can ask about with their descriptions, and the owner's business terms. Not needed before a normal question. Uses no prompt.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "connection_id": "<connection_id>"
    },
    "name": "describe_available_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
connection_idYesThe data source to describe: a connection_id from list_connections or an earlier result.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / connection_id / description
      Added value: +"The data source to describe: a connection_id from list_connections or an earlier result."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing that the result shape varies by source type — Odoo returns readable business areas plus explicitly unsupported areas and example questions, while SQL sources return tables, descriptions, and owner business terms. It does not mention limits on result size, but for a describe/metadata call that is a minor gap.

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 usage trigger is front-loaded and the per-source result breakdown is compact. The telegraphic fragments ("Odoo: ...", "PostgreSQL / MySQL: ...") are efficient, though "Uses no prompt" is terse to the point of ambiguity and slightly interrupts the flow.

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?

For a single-parameter read-only introspection tool with no output schema, the description covers everything an agent needs: the trigger, the required id and its provenance, and what comes back for each supported source type. The per-source result summary compensates well for the absent output schema.

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 coverage is 100% and the schema already states connection_id must come from list_connections or an earlier result, so the description's "Takes the connection_id of the data source (from list_connections)" largely restates it. It does tie the parameter's meaning to source-specific output, but adds no format or validation 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.

Purpose5/5

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

The description opens with a concrete trigger ("when the user asks what they can ask, or whether something is covered") and names the resource being described (Odoo business areas, PostgreSQL/MySQL tables). It is clearly distinct from the sibling question-answering tools, and even states "Not needed before a normal question," which separates it from ask_question.

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?

It gives explicit when-to-use triggers with examples ("a specific Odoo app, or a table"), an explicit when-not-needed case ("Not needed before a normal question"), and routes the agent to list_connections for the required connection_id. No inference is required to choose this tool.

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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