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agy_computer_use.mcp_server

agy_computer_use.mcp_server

by orakulzero
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

cu_type

Types Unicode text into Windows applications by synthesizing keyboard input via Win32 KEYEVENTF_UNICODE, with an optional dry run to test without OS dispatch.

Instructions

Synthesize Unicode keyboard text entry via Win32 KEYEVENTF_UNICODE.

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": {
      "text": "<text>"
    },
    "name": "cu_type"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesText string to type.
dry_runNoSynthesize without OS dispatch.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions the low-level Win32 Unicode injection mechanism, but omits whether an active/focused window is required, what side effects occur, how dry_run changes behavior, and whether OS-level input is actually dispatched in normal use.

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?

The definition is a single, front-loaded sentence with no redundant or filler content. It is appropriately sized for a simple two-parameter tool.

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?

The description is adequate for a simple tool whose parameters are fully documented in the schema, but it leaves out operational context such as focus requirements and dry_run semantics. For a no-annotation mutation/input tool, that gap is noticeable even at low complexity.

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 100%, so both parameters are already documented in the input schema. The description adds no parameter-specific details beyond the schema, which meets the baseline for fully covered schemas.

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 states a specific action (synthesize keyboard text entry) and names the underlying mechanism (Win32 KEYEVENTF_UNICODE), so the agent can tell this is a text-input tool. It does not explicitly differentiate itself from sibling tools like cu_hotkey or cu_click, which keeps it below a 5.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as cu_hotkey, cu_click, or other input tools. The agent can infer it is for typing Unicode text, but no exclusions, prerequisites, or alternative-selection criteria are provided.

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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