eLabFTW MCP

suggest_metadata

Generate structured custom-field suggestions for an eLabFTW experiment or item, then pass them to update_entity_metadata to save changes. Read-only; no data is written.

Instructions

Suggest structured metadata (custom fields) for an eLabFTW experiment or item. Read-only — writes nothing; feed the result into update_entity_metadata to persist it.

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": {
      "entity_type": "<entity_type>",
      "id": "<id>"
    },
    "name": "suggest_metadata"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes
`entity_type`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 7, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations provided, the description carries the behavioral burden and does so by explicitly declaring 'Read-only — writes nothing'. It also discloses the follow-up persistence path via 'update_entity_metadata'. It does not cover auth requirements or whether the target entity must already exist, but the key safety trait is clearly stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the action and scope, followed by the critical read-only and persistence guidance. No filler.

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

Completeness4/5

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 described, and the read-only nature plus the persistence sibling are covered. The remaining gap is the lack of any parameter explanation, which is a real but bounded omission for a two-parameter tool.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the two undocumented parameters. While 'experiment or item' loosely hints at the 'entity_type' values, neither 'entity_type' nor 'id' is explained with format, allowed values, or meaning.

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 states a specific verb and resource ('Suggest structured metadata (custom fields) for an eLabFTW experiment or item') and immediately names the persisting sibling 'update_entity_metadata'. An agent can distinguish this read-only suggestion tool from the write tool without inspecting schemas.

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

Usage Guidelines4/5

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

It clearly describes the intended workflow: use this to generate suggestions, then feed the result into 'update_entity_metadata' to persist. It does not state explicit exclusions versus sibling tools like 'suggest_tags', but the context of use is clear.

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