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control-expert-mcp

control-expert-mcp

by apexsotjo-blip
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

new_project

Create a new PLC project by specifying a valid CPU part number and firmware version. The project is held in memory until saved.

Instructions

Create a new project from scratch for a given PLC CPU.

cpu_part_number must exactly match a CPU reference in the installed Control Expert hardware catalog, e.g. 'BMX P34 2020' (M340), 'BME P58 2040' (M580), 'TSX P57 4634M' (Premium), '140 CPU 651 60' (Quantum). cpu_version is the firmware version offered by the catalog and is required, e.g. '02.70'. The project exists only in memory until save_project is called with a path.

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": {
      "cpu_part_number": "<cpu_part_number>",
      "cpu_version": "<cpu_version>"
    },
    "name": "new_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
cpu_part_numberYes
cpu_versionYes
project_nameNoProject

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the project exists only in memory until saved, which is a critical behavioral trait. It also specifies exact match requirements for cpu_part_number.

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 purpose, no wasted words. Every sentence adds value.

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 tool with 3 parameters, no output schema, and no annotations, the description covers creation, persistence, and parameter constraints fully. An agent can use it correctly.

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?

With 0% schema description coverage, the description adds significant meaning by explaining that cpu_part_number must match the catalog and providing examples, requiring cpu_version, and noting the default for project_name.

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 clearly states 'Create a new project from scratch for a given PLC CPU.' with specific verb and resource. It distinguishes from sibling tools like save_project and open_project by specifying the creation scope.

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?

The description provides clear context on when to use the tool and includes important follow-up action (call save_project). It does not explicitly state when not to use it, but the context is sufficient.

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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