eLabFTW MCP

create_experiment

Create a new eLabFTW experiment and return its ID; requires create write scope and valid category/status IDs, unless team templates are enforced.

Instructions

Create a new eLabFTW experiment. WRITE OPERATION — requires the create write scope. Discover valid category/status IDs first; never embed IDs in the title or body. If the team enforces experiment templates (force_exp_tpl), this tool is refused and create_experiment_from_template must be used. Returns the new id.

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": "create_experiment"
  }
}

Input Schema

Name	Required	Default
`body`	No
`tags`	No
`title`	No	Untitled
`status_id`	No
`category_id`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 7, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and largely meets it: it flags this as a WRITE OPERATION, names the required create write scope, and discloses a refusal condition (force_exp_tpl). It stops short of describing failure/error behavior beyond that one gate or any side effects on templates/metadata, so it is strong but not exhaustive.

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?

Four short sentences, front-loaded with the write/scope requirement and escalating to prerequisites and refusal conditions. Every sentence carries distinct, load-bearing information with 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 and the description still confirms the return shape ('Returns the new id'). Combined with the write-scope, ID-discovery, and template-refusal guidance, an agent has what it needs to call this correctly; only the tags/body semantics remain thin.

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 0%, so the description must compensate; it usefully explains that status_id/category_id must be discovered from valid IDs and warns against embedding IDs in title/body. However, it says nothing about tags, body content format, or the default 'Untitled' title, leaving several parameters undocumented in both schema and description.

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 and resource (create a new eLabFTW experiment) and immediately contrasts itself with the template-based sibling by naming it. An agent can distinguish create_experiment from create_experiment_from_template without opening either definition.

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 explicit when-not guidance: if force_exp_tpl is enforced the tool is refused and create_experiment_from_template must be used instead. It also states a prerequisite (look up valid category/status IDs first), which is actionable routing and preparation guidance rather than inference.

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