MBEstudio

Build full system

build_full_system

Idempotent

Generate the system model, build its existing 3D geometry, verify requirements and allocations, and run selected declared simulations in one prepaid job. Paid. Call it directly: it charges what the job uses, never more than its estimated maximum or the max_spend_credits you set. request_id is optional; set one to make a retry safe. estimate_cost is optional and free, and with cost_mode "agent_authored" it validates a specification without running it. Returns job_id immediately. Poll get_job_status for later progress.

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": "build_full_system"
  }
}

Input Schema

Name	Required	Description	Default
`rows`	No	Only for cost_mode "agent_authored" on generate_safety_analysis: {conditions:[{target,description,severity,...}],modes:[{target,mode,severity,occurrence,detection,...}]}; with analysis "stpa": {losses:[{id,description}],hazards:[{id,description,losses}],controllers:[{target,processModel}],controlActions:[{from,to,name,ucas:[{id,type,context,contextVariables,hazards,constraint}\|{type,notApplicable,rationale}]}],feedback:[{from,to,name,updates}],constraints:[{id,name,text}]}.
`model`	No
`study`	No
`events`	No
`format`	No
`prompt`	No
`stop_s`	No
`analysis`	No	For generate_safety_analysis: fha, fmea, both (default) or stpa. stpa needs no standard.
`fidelity`	No
`model_id`	No	A model from a generation job (model_ id) or a saved studio model (m_ id); a saved model is read at the head of main.
`provider`	No
`standard`	No
`cost_mode`	No		managed
`max_depth`	No	Only for run_agent_swarm: levels of division, 1 to 3 (default 2). At 2 and 3, a subsystem the orchestrator judges too large for one agent is divided again inside its frozen boundary.
`subsystem`	No	For reprompt_agent: qualified name of the subsystem, e.g. "Rover::DriveUnit". For run_agent_swarm on a saved model: the subsystem to decompose one level further (its parts get the agents); leave it out to work on the whole system's subsystems.
`request_id`	No
`scenario_id`	No
`simulations`	No
`specification`	No	Required for cost_mode "agent_authored" on generate_system_model and build_full_system: the system you wrote, as JSON matching this schema (the same schema describe_mbestudio returns as specification_schema). estimate_cost validates it for free with the same checks the paid tools run and lists every problem as a blocker, so call it before a paid tool.
`simulation_type`	No
`max_spend_credits`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedNov 4, 2026

addedInput schema / properties / analysis / description

Added value: +"For generate_safety_analysis: fha, fmea, both (default) or stpa. stpa needs no standard."

changedInput schema / properties / analysis / enum

Previous value: -[
-  "fha",
-  "fmea",
-  "both"
-]New value: +[
+  "fha",
+  "fmea",
+  "both",
+  "stpa"
+]

changedInput schema / properties / rows / description

Previous value: -"Only for cost_mode \"agent_authored\" on generate_safety_analysis: {conditions:[{target,description,severity,...}],modes:[{target,mode,severity,occurrence,detection,...}]}."New value: +"Only for cost_mode \"agent_authored\" on generate_safety_analysis: {conditions:[{target,description,severity,...}],modes:[{target,mode,severity,occurrence,detection,...}]}; with analysis \"stpa\": {losses:[{id,description}],hazards:[{id,description,losses}],controllers:[{target,processModel}],controlActions:[{from,to,name,ucas:[{id,type,context,contextVariables,hazards,constraint}|{type,notApplicable,rationale}]}],feedback:[{from,to,name,updates}],constraints:[{id,name,text}]}."

First observedNov 3, 2026

TDQS

B3.4/5.0

Behavior4/5

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

Beyond the annotations it discloses that the job is paid, charges only actual usage capped at the estimate or max_spend_credits, that request_id makes retries safe, that it returns job_id immediately (async), and that estimate_cost is free and can validate an agent_authored spec. These are substantive behavioral facts not derivable from the annotations. It remains consistent with idempotentHint=true via the request_id retry note.

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?

It is a single dense paragraph that front-loads the core action, then layers cost, idempotency, validation, and the return contract in a logical order. Given the tool's complexity the length is justified, with little filler.

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?

For a 21-parameter paid composite job with no output schema, the description covers cost model, async polling, and validation adequately. But it omits how 'selected declared simulations' are chosen, the role of format/prompt/study params, and when the bundled job beats the granular siblings, leaving meaningful gaps for a tool this complex.

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?

With 21 parameters and only 29% schema description coverage, the description compensates for only a few: request_id (retry safety), cost_mode/agent_authored validation, and max_spend_credits (cost cap). Core parameters like model, study, events, format, prompt, simulations, fidelity, provider, and standard are left undocumented in both the description and their schema entries.

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?

The description names specific verbs and resources: generate the system model, build 3D geometry, verify requirements and allocations, and run simulations 'in one prepaid job.' This clearly frames it as a composite pipeline rather than a single step, though it never explicitly contrasts itself with siblings like generate_system_model, build_3d_model, verify_model, or run_simulation.

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

Usage Guidelines3/5

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

'Call it directly' and the note that estimate_cost can validate a specification for free give some when-to-use direction, plus routing to get_job_status for progress. However, there is no guidance on when to prefer this bundled job over the individual sibling tools, leaving the main selection decision implicit.

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

All MBEstudio tools Inspect

Try in Browser

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?