Skip to main content
Glama
misbahsy

Video & Audio Editing MCP Server

by misbahsy

convert_video_format

Convert a video file to a desired format by specifying input and output paths. Use this tool for efficient video format transformation across formats like MP4, MOV, or AVI. Works with FFmpeg for reliable processing.

Instructions

Converts a video file to the specified target format, attempting to copy codecs first. Args: input_video_path: Path to the source video file. output_video_path: Path to save the converted video file. target_format: Desired output video format (e.g., 'mp4', 'mov', 'avi'). Returns: A status message indicating success or failure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_video_pathYes
output_video_pathYes
target_formatYes

Implementation Reference

  • The main execution function (handler) for the convert_video_format tool. It defines the input schema via type hints and implements the logic using FFmpeg with codec copy preference, calling a helper for execution.
    def convert_video_format(input_video_path: str, output_video_path: str, target_format: str) -> str:
        """Converts a video file to the specified target format, attempting to copy codecs first.
        Args:
            input_video_path: Path to the source video file.
            output_video_path: Path to save the converted video file.
            target_format: Desired output video format (e.g., 'mp4', 'mov', 'avi').
        Returns:
            A status message indicating success or failure.
        """
        primary_kwargs = {'format': target_format, 'vcodec': 'copy', 'acodec': 'copy'}
        fallback_kwargs = {'format': target_format} # Re-encode both streams
        return _run_ffmpeg_with_fallback(input_video_path, output_video_path, primary_kwargs, fallback_kwargs)
  • Supporting helper function that implements the FFmpeg execution logic with fallback from stream-copy to re-encoding, used by convert_video_format and similar tools.
    def _run_ffmpeg_with_fallback(input_path: str, output_path: str, primary_kwargs: dict, fallback_kwargs: dict) -> str:
        """Helper to run ffmpeg command with primary kwargs, falling back to other kwargs on ffmpeg.Error."""
        try:
            ffmpeg.input(input_path).output(output_path, **primary_kwargs).run(capture_stdout=True, capture_stderr=True)
            return f"Operation successful (primary method) and saved to {output_path}"
        except ffmpeg.Error as e_primary:
            try:
                ffmpeg.input(input_path).output(output_path, **fallback_kwargs).run(capture_stdout=True, capture_stderr=True)
                return f"Operation successful (fallback method) and saved to {output_path}"
            except ffmpeg.Error as e_fallback:
                err_primary_msg = e_primary.stderr.decode('utf8') if e_primary.stderr else str(e_primary)
                err_fallback_msg = e_fallback.stderr.decode('utf8') if e_fallback.stderr else str(e_fallback)
                return f"Error. Primary method failed: {err_primary_msg}. Fallback method also failed: {err_fallback_msg}"
        except FileNotFoundError:
            return f"Error: Input file not found at {input_path}"
        except Exception as e:
            return f"An unexpected error occurred: {str(e)}"
  • server.py:351-351 (registration)
    The @mcp.tool() decorator registers the convert_video_format function as an MCP tool with FastMCP.
    def convert_video_format(input_video_path: str, output_video_path: str, target_format: str) -> str:
  • The function signature and docstring define the input schema and description for the MCP tool, used by FastMCP to generate JSON schema.
    def convert_video_format(input_video_path: str, output_video_path: str, target_format: str) -> str:
        """Converts a video file to the specified target format, attempting to copy codecs first.
        Args:
            input_video_path: Path to the source video file.
            output_video_path: Path to save the converted video file.
            target_format: Desired output video format (e.g., 'mp4', 'mov', 'avi').
        Returns:
            A status message indicating success or failure.
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the tool's behavior ('attempting to copy codecs first') and output ('status message indicating success or failure'), but lacks details on permissions, rate limits, error handling, or what happens to the original file. This is adequate but has gaps 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a purpose statement, Args section, and Returns section, making it easy to parse. It's appropriately sized with no redundant information, though the 'attempting to copy codecs first' detail could be more integrated into the flow.

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 mutation tool with no annotations, no output schema, and 0% schema coverage, the description is moderately complete. It covers purpose, parameters, and return type, but lacks behavioral details like side effects, error cases, or performance considerations, which are important for a video conversion operation.

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?

Schema description coverage is 0%, so the description must compensate. It clearly explains all three parameters: input_video_path ('Path to the source video file'), output_video_path ('Path to save the converted video file'), and target_format ('Desired output video format' with examples). This adds significant meaning beyond the bare schema.

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 the tool's purpose with specific verbs ('converts', 'attempting to copy codecs') and resources ('video file', 'target format'), distinguishing it from siblings like convert_audio_format or convert_video_properties by focusing on format conversion rather than property changes.

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?

The description implies usage for video format conversion but doesn't explicitly state when to use this tool versus alternatives like convert_video_properties or set_video_codec. It mentions 'attempting to copy codecs first', which hints at a specific approach, but lacks clear exclusions or named alternatives.

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

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/misbahsy/video-audio-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server