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io.github.legolev/mediamcp

NPM · MEDIAMCP · SCANNED SEP 20

Generate and edit images and video via OpenRouter or any OpenAI-compatible API.

Available components

0 this week 92 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security98
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • No install/post-install scripts declared.Pass
  • 51 of 157 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency100
  • Source repository is publicly reachable at the declared URL. View diagnostics → Pass
  • Cryptographically verified build provenance (signed, bound to legolev/mediamcp). View diagnostics → Pass
  • Clear OSI-approved license (MIT).Pass
  • Actively maintained (last published 32 days ago).Pass
  • Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability71
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 1322 tokens (~220/item across 6 items; 6 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management87
  • Stability observed for 26 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 6 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 7 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

How do I install the io.github.legolev/mediamcp MCP server?

io.github.legolev/mediamcp runs locally as an npm package, launched with npx -y mediamcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

npm · mediamcp

# add to Claude Code
claude mcp add legolev-mediamcp -- npx -y mediamcp
// .cursor/mcp.json
{
  "mcpServers": {
    "legolev-mediamcp": {
      "command": "npx",
      "args": [
        "-y",
        "mediamcp"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "legolev-mediamcp": {
      "command": "npx",
      "args": [
        "-y",
        "mediamcp"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add legolev-mediamcp -- npx -y mediamcp
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "legolev-mediamcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "mediamcp"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add legolev-mediamcp --command npx --arg -y --arg mediamcp
# ~/.hermes/config.yaml
mcp_servers:
  legolev-mediamcp:
    command: "npx"
    args: ["-y", "mediamcp"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "legolev-mediamcp": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "mediamcp"
      ]
    }
  }
}
# add to Vellum
assistant mcp add legolev-mediamcp -t stdio -c npx -a -y mediamcp
// mcp.json
{
  "mcpServers": {
    "legolev-mediamcp": {
      "command": "npx",
      "args": [
        "-y",
        "mediamcp"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 19 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.

  • 18 Sept 26 −3
    • Stability: pass → 0.80 functional
  • 17 Sept 26 0
    • Stability: 0.97 → pass security
  • 16 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

  • 14 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.

  • 12 Sept 26 −2
    • Stability: pass → 0.83 functional
  • 11 Sept 26 0
    • Stability: 0.97 → pass security
  • 10 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 20 Sept 2026 · Analysed npm/mediamcp@0.3.0

Provenance Verified

A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.

Result Verified
Ecosystem npm
Reason Verified
Discovered via Registry attestation endpoint
Source repo legolev/mediamcp
Certificate issuer https://token.actions.githubusercontent.com
Certificate SAN https://github.com/legolev/mediamcp/.github/workflows/release.yml@refs/tags/v0.3.0
Rekor log index 2501455372
Predicate type https://slsa.dev/provenance/v1
Subject digest sha512:ed9a9073d0b2ca708006d13a66453819d1877d0aacd0ae7dd624499a1b35497606fe74cbfc8672c58cef42edfe444e6425005b57fb48dc12eafca33ad

Background: How many MCP packages publish verified provenance →

Dependencies 157 packages
Packages resolved 157
Stale 51
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 6 exposed · ~1,256 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
check_config ~64

Diagnose the mediamcp server setup: endpoint, API key presence and validity, default models, and output directory writability. Run this first when any other mediamcp tool fails.

NameTypeReqDescription
pingbooleanAlso verify the API key against the endpoint with a live request.
NameTypeReqDescription
api_keystringyesMasked key or 'not set'
api_key_sourcestring
base_urlstringyes
image_modelstringyes
key_checkstring
okbooleanyes
output_dirstringyes
output_dir_writablebooleanyes
previewstringyes
problemsarrayyes
schema_dialectstringyesJSON Schema dialect the tool schemas are advertised in
versionstringyes
video_modelstringyes

No examples provided.

check_video_status ~136

Check a previously started video generation job (from generate_video's polling_url or video id). If the job has completed, downloads the video, saves it to disk, and returns the absolute path.

NameTypeReqDescription
filename_prefixstringShort label used in the saved filename, e.g. 'hero-banner'. Sanitized to letters, digits, dashes.
output_dirstringDirectory to save into (absolute, or ~ for home). Defaults to the configured output directory.
polling_urlstringThe polling_url returned by generate_video.
video_idstringAlternatively, the raw video job id.
NameTypeReqDescription
messagestring
pathstringAbsolute path of the saved video, when completed
polling_urlstringPass to check_video_status to resume waiting
statusstringyescompleted | pending | in_progress | timeout | failed | error
video_idstring

No examples provided.

edit_image ~238

Edit or transform existing image(s) with a text instruction — restyle, add or remove elements, change background, or combine several images into one scene. The result is saved to disk and its absolute path is returned, along with a small inline preview.

NameTypeReqDescription
filename_prefixstringShort label used in the saved filename, e.g. 'hero-banner'. Sanitized to letters, digits, dashes.
imagesarrayyesSource image(s): absolute file paths, file:// URLs, https:// URLs, or data: URLs. Pass several images for composition or style-transfer edits.
modelstringModel slug, e.g. 'google/gemini-2.5-flash-image' or 'openai/gpt-5-image'. Omit to use the configured default. Call list_models to see options.
output_dirstringDirectory to save into (absolute, or ~ for home). Defaults to the configured output directory.
promptstringyesInstruction describing the edit, e.g. 'remove the background', 'make it night time', 'combine these two photos into one scene'.
NameTypeReqDescription
failedarrayyesError messages for variations that failed
imagesarrayyes

No examples provided.

generate_image ~231

Generate one or more images from a text prompt using a cloud AI model. Every image is saved to disk and its absolute path is returned, along with a small inline preview. Use edit_image instead when starting from an existing image.

NameTypeReqDescription
aspect_ratiostringDesired aspect ratio. Support varies by model; treated as a strong hint.
countintegerNumber of variations to generate (1-4, parallel requests, billed per image).
filename_prefixstringShort label used in the saved filename, e.g. 'hero-banner'. Sanitized to letters, digits, dashes.
modelstringModel slug, e.g. 'google/gemini-2.5-flash-image' or 'openai/gpt-5-image'. Omit to use the configured default. Call list_models to see options.
output_dirstringDirectory to save into (absolute, or ~ for home). Defaults to the configured output directory.
promptstringyesDetailed description of the desired result. Be specific about subject, style, lighting, composition.
NameTypeReqDescription
failedarrayyesError messages for variations that failed
imagesarrayyes

No examples provided.

generate_video ~519

Generate a video from a text prompt, and optionally from an input image (image-to-video). Async job: starts generation, then waits and polls. Video generation typically takes 1-5 minutes. The finished file is saved to disk and its absolute path is returned. If waiting times out, a polling_url is returned — pass it to check_video_status later instead of starting a new (billed) job. For image-to-video, pass first_frame_image so the clip animates from that exact picture (e.g. a still produced by generate_image). Image inputs require an image-to-video-capable model such as 'bytedance/seedance-2.0', 'bytedance/seedance-2.0-fast', or 'google/veo-3.1'.

NameTypeReqDescription
aspect_ratiostringDesired aspect ratio. Support varies by model; treated as a strong hint.
duration_secondsintegerClip length in seconds (model-dependent).
filename_prefixstringShort label used in the saved filename, e.g. 'hero-banner'. Sanitized to letters, digits, dashes.
first_frame_imagestringImage-to-video: the generated clip starts on this exact image and animates forward. Accepts an absolute file path, file:// URL, https:// URL, or data: URL.
generate_audiobooleanWhether the clip should include generated audio.
last_frame_imagestringOptional ending frame the clip animates toward. Same accepted formats as first_frame_image.
modelstringVideo model slug, e.g. 'google/veo-3.1' or 'openai/sora-2-pro'. For image-to-video use an i2v-capable model like 'bytedance/seedance-2.0' or 'bytedance/seedance-2.0-fast'. Omit to use the configured…
output_dirstringDirectory to save into (absolute, or ~ for home). Defaults to the configured output directory.
promptstringyesDetailed description of the desired result. Be specific about subject, style, lighting, composition.
reference_imagesarrayStyle/content reference image(s) that guide the look without being exact frames (reference-to-video). Same accepted formats as first_frame_image.
resolutionstringOutput resolution (model-dependent).
wait_secondsintegerHow long to wait for completion before returning a resumable polling_url.
NameTypeReqDescription
messagestring
pathstringAbsolute path of the saved video, when completed
polling_urlstringPass to check_video_status to resume waiting
statusstringyescompleted | pending | in_progress | timeout | failed | error
video_idstring

No examples provided.

list_models ~68

List image- and video-capable model slugs available on the configured endpoint, with pricing where known. Use this to pick a `model` value for generate_image, edit_image, or generate_video.

NameTypeReqDescription
refreshbooleanBypass the 1h cache and re-query the endpoint.
NameTypeReqDescription
modelsarrayyes
notestring
sourcestringyes'live' = queried from the endpoint, 'curated' = built-in fallback

No examples provided.

Common questions

What is the io.github.legolev/mediamcp MCP server?

io.github.legolev/mediamcp is an MCP server listed in the public MCP registry as io.github.legolev/mediamcp. Generate and edit images and video via OpenRouter or any OpenAI-compatible API. This page covers its npm package (mediamcp).

Is the io.github.legolev/mediamcp MCP server safe to use?

io.github.legolev/mediamcp scores 92 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. It declares no install or post-install scripts. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the io.github.legolev/mediamcp MCP server expose?

io.github.legolev/mediamcp exposes 6 tools: generate_image, edit_image, generate_video, check_video_status, list_models, check_config. Their descriptions and schemas cost roughly 1,256 tokens of context every time the server is loaded.

Is the io.github.legolev/mediamcp MCP server still maintained?

io.github.legolev/mediamcp is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the io.github.legolev/mediamcp MCP server under?

io.github.legolev/mediamcp declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.