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Windows TTS MCP Server

by balloonf

stop_speech

Stop all currently playing speech instantly using this tool, designed for precise playback control in Windows TTS MCP Server. Ideal for managing text-to-speech interruptions effectively.

Instructions

현재 재생 중인 모든 음성을 중지합니다

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'stop_speech' tool. It terminates all running TTS processes managed in the global 'running_processes' list, clears the list, and additionally kills PowerShell processes containing 'Speech' in their command line.
    @mcp.tool()
    def stop_speech() -> str:
        """현재 재생 중인 모든 음성을 중지합니다"""
        try:
            stopped_count = 0
            
            with process_lock:
                # 실행 중인 모든 TTS 프로세스 종료
                for process in running_processes[:]:  # 복사본으로 순회
                    try:
                        if process.poll() is None:  # 아직 실행 중인 프로세스
                            process.terminate()
                            time.sleep(0.1)
                            if process.poll() is None:  # 여전히 실행 중이면 강제 종료
                                process.kill()
                            stopped_count += 1
                        running_processes.remove(process)
                    except Exception as e:
                        safe_print(f"프로세스 종료 오류: {e}")
                
                running_processes.clear()
            
            # PowerShell 프로세스도 강제 종료
            try:
                # Windows에서 모든 PowerShell TTS 프로세스 찾아서 종료
                subprocess.run([
                    "powershell", "-Command",
                    "Get-Process | Where-Object {$_.ProcessName -eq 'powershell' -and $_.CommandLine -like '*Speech*'} | Stop-Process -Force"
                ], capture_output=True, timeout=5)
            except:
                pass
            
            if stopped_count > 0:
                return f"[STOP] {stopped_count}개의 음성 재생을 중지했습니다"
            else:
                return "[INFO] 현재 재생 중인 음성이 없습니다"
                
        except Exception as e:
            return f"[ERROR] 음성 중지 오류: {str(e)}"
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool stops speech but doesn't describe what 'stop' means operationally (pause vs terminate, immediate vs graceful), whether it requires specific permissions, what happens to queued speech, or what response to expect. For a zero-parameter tool with no annotations, this leaves significant behavioral questions unanswered.

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 description is a single, efficient sentence that directly states the tool's function without any wasted words. It's appropriately sized for a simple, zero-parameter tool and gets straight to the point.

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 zero-parameter tool with no output schema, the description provides the basic purpose but lacks important context. It doesn't explain what constitutes 'speech' in this context, whether the stop is reversible, what confirmation (if any) is provided, or how this differs from similar sibling tools. Given the tool's apparent simplicity, the description is minimally adequate but could be more complete.

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?

The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents the empty parameter set.

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 clearly states the action ('중지합니다' - stops) and target ('현재 재생 중인 모든 음성' - all currently playing speech), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'emergency_silence' or 'kill_all_tts' which may have similar functions, preventing a perfect score.

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?

The description provides minimal guidance - it implies usage when speech is currently playing, but offers no explicit when/when-not instructions or alternatives. There's no mention of when to use this versus similar tools like 'emergency_silence' or 'kill_all_tts', nor any prerequisites or exclusions.

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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