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media convert

media_convert
Read-only

Convert audio or video between formats with ffmpeg: mp4, webm, mov, mkv, mp3, wav, ogg, opus, m4a, aac, flac. Optional width, fps, crf, audio_bitrate, sample_rate and channels. Up to 20 MB in, 150 s of processing. Costs $0.018 USDC per call (x402).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesmp4, webm, mov, mkv, mp3, wav, ogg, opus, m4a, aac, flac
crfNo15-45, lower = better quality
fpsNo
urlNohttps URL of the file (max 20 MB)
storeNoReturn 7-day share links instead of base64 (+$0.001); automatic above 3 MB
widthNo
formatNobinary = raw file bytes (single output)
channelsNo
filenameNoName with extension, helps detect the type
file_base64NoOr the file as base64 / data URI
sample_rateNo
audio_bitrateNoe.g. 128k

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Goes well beyond the sparse readOnlyHint/openWorldHint annotations by disclosing the 20 MB input cap, the 150 s processing budget, and the per-call x402 price of $0.018 USDC — all of which the agent needs before committing. It stops short of describing how input is supplied or what the response looks like (base64 vs stored link), which the schema only partially covers.

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?

Three tight sentences with the capability, the format list, the tunables, then limits and price — front-loaded and free of filler. The format enumeration is long but directly actionable rather than padding.

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

Completeness4/5

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

For a 12-parameter tool with no output schema, the description covers the two things the schema does not: cost model and hard resource limits. It omits input-source selection (url vs file_base64 vs filename) and output delivery semantics, but those are the most richly documented schema properties, so the gap is tolerable.

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 67%, so the schema already documents the important params (to, url, store, crf, filename, format, file_base64). The description mostly re-lists optionals (width, fps, crf, audio_bitrate, sample_rate, channels) without adding ranges, defaults, or interactions such as video-vs-audio-only applicability, so it is baseline-value only.

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?

States a specific verb and resource (convert audio/video between formats via ffmpeg) and enumerates the supported container/codec set, so the agent knows exactly what the tool produces. It never names or contrasts the close siblings (media_trim, media_extract_audio, convert, image_convert), so sibling differentiation is left to inference.

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 explicit when-to-use guidance and no alternatives are named, even though the sibling list contains near-identical converters (convert, media_extract_audio, media_trim). Limits are stated but they are operating constraints, not selection criteria.

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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