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FFmpeg MCP Server

FFmpeg MCP Server

Diese README-Datei enthält Informationen zum ffmpeg-mcp -Repository, das einen MCP-Server für FFmpeg enthält. Nachfolgend finden Sie Details zum Repository sowie einen Link zu den neuesten Versionen.

🌟 Über das Repository

Repository-Name: ffmpeg-mcp

Kurzbeschreibung: Ein MCP-Server für FFmpeg

Themen: Nicht bereitgestellt

Related MCP server: Project Content Server

🚀 Erste Schritte

Um auf die neuesten Versionen des MCP-Servers für FFmpeg zuzugreifen, klicken Sie auf den folgenden Link:

MCP-Server herunterladen

Wenn der Link einen Pfadteil enthält, laden Sie die angegebene Datei herunter und führen Sie sie aus, um den MCP-Server zu verwenden.

Wenn der Link nur die Domäne enthält, besuchen Sie einfach den bereitgestellten Link, um die neuesten Versionen zu erkunden und herunterzuladen.

Wenn der angegebene Link nicht funktioniert oder nicht von Ihnen bereitgestellt wurde, empfehlen wir Ihnen, im Abschnitt „Releases“ dieses Repositorys nach den neuesten Updates zu suchen.

📦 Funktionen

Hier sind einige Hauptfunktionen des ffmpeg-mcp- Repository:

  • MCP-Serverkompatibilität: Speziell für die nahtlose Zusammenarbeit mit FFmpeg entwickelt.

  • Verbesserte Leistung: Optimiert für Effizienz und Geschwindigkeit bei Medienverarbeitungsaufgaben.

  • Sichere Kommunikation: Implementiert sichere Kommunikationsprotokolle für die Datenübertragung.

  • Skalierbare Architektur: Entwickelt, um große Mengen an Medienverarbeitungsanforderungen zu verarbeiten.

🛠️ Installation

Um den MCP-Server für FFmpeg zu installieren, gehen Sie folgendermaßen vor:

  1. Laden Sie die neueste Version über den bereitgestellten Link herunter.

  2. Führen Sie die heruntergeladene Datei aus, um den Installationsvorgang zu starten.

  3. Befolgen Sie die Anweisungen auf dem Bildschirm, um die Installation abzuschließen.

  4. Beginnen Sie, den MCP-Server mit FFmpeg für Ihre Medienverarbeitungsanforderungen zu verwenden.

📜 Verwendung

Nach der Installation können Sie den MCP-Server mit FFmpeg verwenden, indem Sie die folgenden Schritte ausführen:

  1. Konfigurieren Sie die Servereinstellungen entsprechend Ihren Anforderungen.

  2. Verbinden Sie den Server mit Ihrer FFmpeg-Umgebung.

  3. Beginnen Sie mit dem Senden von Medienverarbeitungsaufgaben zur Ausführung an den MCP-Server.

  4. Überwachen Sie den Fortschritt und die Leistung des Servers über die bereitgestellte Schnittstelle.

📈 Roadmap

Zukünftige Updates für den MCP-Server in diesem Repository können Folgendes umfassen:

  • Integration mit zusätzlichen Medienverarbeitungstools.

  • Verbesserte Sicherheitsfunktionen zum Datenschutz.

  • Leistungsoptimierungen für schnellere Verarbeitungsgeschwindigkeiten.

  • Verbesserte Skalierbarkeit für die Bewältigung größerer Arbeitslasten.

🤝 Beitragen

Wenn Sie daran interessiert sind, zur Entwicklung des MCP-Servers in diesem Repository beizutragen, befolgen Sie bitte diese Richtlinien:

  • Forken Sie das Repository und nehmen Sie die gewünschten Änderungen vor.

  • Senden Sie eine Pull-Anfrage mit einer detaillierten Beschreibung der Änderungen.

  • Ihre Beiträge werden von den Repository-Betreuern auf eine mögliche Aufnahme geprüft.

📧 Kontakt

Wenn Sie Fragen, Feedback oder Vorschläge zum MCP-Server für FFmpeg in diesem Repository haben, können Sie sich gerne unter developer@example.com an uns wenden.


Mit dieser README-Datei können Sie schnell mit dem ffmpeg-mcp -Repository loslegen und die Funktionen des MCP-Servers für Ihre Medienverarbeitungsaufgaben nutzen. Detailliertere Informationen finden Sie in den Dateien, der Dokumentation und den Releases des Repositorys. Vielen Dank für Ihr Interesse an unserem Projekt! 🎉

Available Tools

2 tools
extract_audioB

Extract audio as mp3 from a video

ParametersJSON Schema
NameRequiredDescriptionDefault
input_fileYesPath to input file
output_fileNoPath to output file, output to the same directory if not specified

TDQS

B3.1/5.0
Behavior2/5

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 mentions the output format (mp3) but lacks details on behavioral traits like error handling, performance constraints, or whether the operation is destructive to the input file. This leaves significant gaps for an agent to understand the tool's behavior.

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 clearly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects and usage context, leaving room for improvement in completeness.

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 the schema already documents both parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as format details or usage examples, resulting in a baseline score of 3.

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 ('extract audio') and the resource ('from a video'), specifying the output format as mp3. However, it doesn't differentiate from the sibling tool 'speed_up', which appears to be a different operation, so it doesn't fully distinguish from siblings.

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?

No guidance is provided on when to use this tool versus alternatives. The description only states what it does, with no context about prerequisites, limitations, or comparison to the sibling tool 'speed_up'.

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

speed_upC

Speed up a video

ParametersJSON Schema
NameRequiredDescriptionDefault
input_fileYesPath to input file
max_fpsNoMax FPS for the output file
output_fileNoPath to output file, output to the same directory if not specified
speed_factorNoSpeed factor for the output file, default to 2x sped up

TDQS

C2.9/5.0
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. While 'speed up' implies a transformation operation, it doesn't disclose whether this is destructive to the original file, what permissions are needed, or any rate limits. The description lacks essential behavioral context for a mutation tool.

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 extremely concise at just three words, front-loading the core purpose without any wasted language. Every word earns its place in this minimal but clear statement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a video processing tool with 4 parameters and no annotations or output schema, the description is insufficient. It doesn't explain what the tool returns, what happens to the original file, or provide any context about the processing operation beyond the basic purpose.

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 the schema already fully documents all four parameters. The description adds no additional parameter information beyond what's in the schema, meeting the baseline expectation but not providing extra value.

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 ('speed up') and resource ('a video'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'extract_audio', which handles a different video processing function.

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?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention the sibling tool 'extract_audio' or any other video processing options, leaving the agent without context for tool selection.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv1.0.0
    • First observedextract_audio
    • First observedspeed_up

TDQS

B3.1/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have completely distinct purposes: one extracts audio from video, while the other modifies video playback speed. There is no overlap in functionality, making it impossible to confuse them.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern (extract_audio, speed_up), using clear action verbs and descriptive nouns. The naming is uniform and predictable throughout the set.

Tool Count2/5

With only two tools, this server is severely under-scoped for an FFmpeg server, which typically handles a wide range of media processing tasks like format conversion, filtering, and metadata editing. The count feels incomplete for the domain.

Completeness1/5

The tool surface is extremely incomplete for an FFmpeg server, lacking core operations such as video format conversion, resolution changes, filtering, metadata extraction, or basic CRUD-like media processing. Agents will face significant gaps in functionality.

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