Media Downloader
CLI or API | MCP
Version: 4.3.1
Documentation — Installation, deployment, and usage across the CLI, Python API, MCP, and A2A agent interfaces are maintained in the official documentation.
Overview
Media Downloader is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with Download audio/videos from the internet! Host an MCP Server for Agentic AI to download videos!.
Key Features
- Consolidated Action-Routed MCP Tools: Minimizes token overhead and eliminates tool bloat in LLM contexts by grouping methods into optimized, togglable tool modules.
- Enterprise-Grade Security: Complete support for Eunomia policies, OIDC token delegation, and granular execution context tracking.
- Integrated Graph Agent: Built-in Pydantic AI agent supporting the Agent Control Protocol (ACP) and standard Web interfaces (AG-UI).
- Native Telemetry & Tracing: Out-of-the-box OpenTelemetry exports and native Langfuse tracing.
CLI or API
This agent wraps the Download audio/videos from the internet! Host an MCP Server for Agentic AI to download videos! API. The operator can interact with it programmatically or via its integrated execution entrypoints.
Detailed instructions on how to use the underlying API wrappers, extended schema bindings, and developer SDK references are maintained in docs/index.md.
MCP
This server use dynamic Action-Routed tools to optimize token overhead and maximize IDE compatibility.
Available MCP Tools
Condensed action-routed tools (MCP_TOOL_MODE=condensed)
| MCP Tool | Toggle Env Var | Description |
|---|---|---|
build_watch_skill |
— | Write a video-built skill, or append another video's findings to one. |
download_media |
— | Download video or audio from supported sites (YouTube, Rumble, etc.). |
list_watch_skills |
— | List video-built skills under a root and the videos each already has. |
watch_media |
— | Watch a video: download it with captions and extract key frames. |
Verbose 1:1 API-mapped tools (MCP_TOOL_MODE=verbose or both)
7 per-operation tools — one per public API method (click to expand)
| MCP Tool | Toggle Env Var | Description |
|---|---|---|
media_downloader_download_all |
MEDIA_DOWNLOADERTOOL |
Invoke the download_all operation. |
media_downloader_download_video |
MEDIA_DOWNLOADERTOOL |
Invoke the download_video operation. |
media_downloader_get_channel_videos |
MEDIA_DOWNLOADERTOOL |
Invoke the get_channel_videos operation. |
media_downloader_open_file |
MEDIA_DOWNLOADERTOOL |
Invoke the open_file operation. |
media_downloader_progress_hook |
MEDIA_DOWNLOADERTOOL |
Invoke the progress_hook operation. |
media_downloader_set_progress_callback |
MEDIA_DOWNLOADERTOOL |
Invoke the set_progress_callback operation. |
media_downloader_watch |
MEDIA_DOWNLOADERTOOL |
Download a video with its captions and extract scene-change key frames. |
4 action-routed tool(s) · 7 verbose 1:1 tool(s). Each is enabled unless its <DOMAIN>TOOL toggle is set false; MCP_TOOL_MODE selects the surface (intent default — the six verb-tools, granular set loaded on demand · condensed action-routed · verbose 1:1 · both). Auto-generated — do not edit.
Detailed tool schemas, parameter shapes, and validation constraints are preserved in docs/usage.md.
Dynamic Tool Selection & Visibility
This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows the operator to restrict the set of exposed tools to prevent blowing up the LLM's context window.
The operator can configure tool filtering via multiple input channels:
- CLI Arguments: Pass
--toolsor--toolsets(or their disabled counterparts--disabled-toolsand--disabled-toolsets) during startup. - Environment Variables: Define standard environment variables:
MCP_ENABLED_TOOLS/MCP_DISABLED_TOOLSMCP_ENABLED_TAGS/MCP_DISABLED_TAGS
- HTTP SSE Request Headers: Pass custom headers during transport initialization:
x-mcp-enabled-tools/x-mcp-disabled-toolsx-mcp-enabled-tags/x-mcp-disabled-tags
- HTTP SSE Request Query Parameters: Append query parameters directly to the operator's transport connection URL:
?tools=tool1,tool2?tags=tag1
When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.
MCP Configuration Examples
Install the connector-focused
[mcp]extra. Examples usemedia-downloader[mcp]to add FastMCP / FastAPI throughagent-connector-sdk; the required Agent Connector SDK core still carriesepistemic-graph[full]. The[agent-runtime]extra additionally enables model orchestration.
stdio Transport (local IDEs — Cursor, Claude Desktop, VS Code)
{
"mcpServers": {
"media-downloader-mcp": {
"command": "uvx",
"args": [
"--from",
"media-downloader[mcp]",
"media-downloader-mcp"
],
"env": {
"MCP_TOOL_MODE": "intent",
"MEDIA_DOWNLOADER_ALLOW_PRIVATE_HOSTS": "media.internal.example",
"MEDIA_DOWNLOADER_MAX_WORKERS": "4",
"MEDIA_DOWNLOADER_OUTPUT_ROOT": "/data/media",
"WORKSPACE_PATH": "/workspace"
}
}
}
}
Runtime references require an alias-aware launcher such as Arbora. Other launchers must omit those entries and inject the resolved values through their own runtime secret boundary.
Streamable-HTTP Transport (networked / production)
{
"mcpServers": {
"media-downloader-mcp": {
"command": "uvx",
"args": [
"--from",
"media-downloader[mcp]",
"media-downloader-mcp",
"--transport",
"streamable-http",
"--port",
"8000"
],
"env": {
"TRANSPORT": "streamable-http",
"HOST": "127.0.0.1",
"PORT": "8000",
"MCP_TOOL_MODE": "intent",
"MEDIA_DOWNLOADER_ALLOW_PRIVATE_HOSTS": "media.internal.example",
"MEDIA_DOWNLOADER_MAX_WORKERS": "4",
"MEDIA_DOWNLOADER_OUTPUT_ROOT": "/data/media",
"WORKSPACE_PATH": "/workspace"
}
}
}
}
Alternatively, connect to a pre-deployed Streamable-HTTP instance by url:
{
"mcpServers": {
"media-downloader-mcp": {
"url": "http://localhost:8000/media-downloader-mcp/mcp"
}
}
}
Run a reviewed container image as a least-privilege stdio child (no listener or published port):
docker run -i --rm \
--read-only \
--cap-drop=ALL \
--security-opt=no-new-privileges \
--pids-limit=256 \
--tmpfs /tmp:rw,noexec,nosuid,nodev,size=64m \
-e TRANSPORT=stdio \
-e MCP_TOOL_MODE=intent \
-e MEDIA_DOWNLOADER_ALLOW_PRIVATE_HOSTS=media.internal.example \
-e MEDIA_DOWNLOADER_MAX_WORKERS=4 \
-e MEDIA_DOWNLOADER_OUTPUT_ROOT=/data/media \
-e WORKSPACE_PATH=/workspace \
registry.example.invalid/media-downloader@sha256:<digest> media-downloader-mcp
For containerized network HTTP, supply an authenticated TLS ingress (or
direct server TLS), exact MCP_ALLOWED_HOSTS, and an exact trusted-proxy
CIDR policy through the operator-owned deployment profile. The generator
does not emit an unauthenticated non-loopback listener.
Auto-generated from the code-read env surface (MCP_TOOL_MODE + package vars) — do not edit.
Additional Deployment Options
media-downloader can run as a local stdio process or container, or behind a remote
network boundary. The
Deployment guide carries
the detailed transport contract.
- Local container — launch a reviewed immutable image as a least-privilege stdio child with no listener or published port.
- Remote URL — connect through an operator-supplied authenticated HTTPS
ingress. Keep its URL, outbound identity references, trust profile, and exact
MCP_ALLOWED_HOSTSinAgentConfig.
Agent
This repository features a fully integrated Pydantic AI Graph Agent. It communicates over the Agent Control Protocol (ACP) and interacts smoothly with the Agent Web UI (AG-UI) and Terminal interface.
Running the Agent CLI
To start the interactive command-line agent:
# Run the agent server
media-downloader-agent --provider openai --model-id gpt-4o
Docker Compose Orchestration
version: '3.8'
services:
media-downloader-mcp:
image: example/media-downloader@sha256:<digest>
container_name: media-downloader-mcp
hostname: media-downloader-mcp
restart: always
env_file:
- ../.env
environment:
- PYTHONUNBUFFERED=1
- HOST=0.0.0.0
- PORT=8000
- TRANSPORT=streamable-http
ports:
- "8000:8000"
healthcheck:
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
interval: 30s
timeout: 10s
retries: 3
start_period: 10s
logging:
driver: json-file
options:
max-size: "10m"
max-file: "3"
image: example/media-downloader@sha256:<digest>
container_name: media-downloader-agent
hostname: media-downloader-agent
restart: always
depends_on:
- media-downloader-mcp
env_file:
- ../.env
command: [ "media-downloader-agent" ]
environment:
- PYTHONUNBUFFERED=1
- HOST=0.0.0.0
- PORT=9000
- MCP_URL=http://media-downloader-mcp:8000/mcp
- PROVIDER=${PROVIDER:-openai}
- MODEL_ID=${MODEL_ID:-gpt-4o}
- ENABLE_WEB_UI=True
- ENABLE_OTEL=True
ports:
- "9000:9000"
healthcheck:
test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9000/health')"]
interval: 30s
timeout: 10s
retries: 3
start_period: 10s
logging:
driver: json-file
options:
max-size: "10m"
max-file: "3"
Detailed graph node architecture explanations, custom skill configurations, and agentic trace guides are available in docs/deployment.md.
Security & Governance
Built directly upon the enterprise-ready agent-connector-sdk core, standard security parameters are fully supported:
Access Control & Policy Enforcement
- Eunomia Policies: Fine-grained, policy-driven tool authorization. Supports
none, localembedded(mcp_policies.json), or centralizedremotemodes. - OIDC Token Delegation: Compliant with RFC 8693 token exchange for flowing authenticating user credentials from Web UI / ACP → Agent → MCP.
- Scoped Credentials: Execution context runs restricted to the specific caller identity.
Runtime Security Grid
| Feature | Feature | Enablement |
|---|---|---|
| Tool Guard | Sensitivity inspection with human-in-the-loop validation | Enabled by default |
| Prompt Injection Defense | Input scanning, repetition monitoring, and recursive loop blocks | Enabled by default |
| Context Safety Guard | Stuck-loop detectors and contextual overflow preemptive alerts | Enabled by default |
Environment Variables
Package environment variables
| Variable | Example | Description |
|---|---|---|
HOST |
0.0.0.0 |
|
PORT |
8000 |
|
TRANSPORT |
stdio |
options: stdio, streamable-http, sse |
ENABLE_OTEL |
True |
|
OTEL_EXPORTER_OTLP_ENDPOINT |
http://localhost:8080/api/public/otel |
|
OTEL_EXPORTER_OTLP_PUBLIC_KEY_REF |
pk-... |
|
OTEL_EXPORTER_OTLP_SECRET_KEY_REF |
sk-... |
|
OTEL_EXPORTER_OTLP_PROTOCOL |
http/protobuf |
|
EUNOMIA_TYPE |
none |
options: none, embedded, remote |
EUNOMIA_POLICY_FILE |
mcp_policies.json |
|
EUNOMIA_REMOTE_URL |
http://eunomia-server:8000 |
|
MEDIA_DOWNLOADER_MCP_IMAGE |
knucklessg1/media-downloader@sha256:<digest> |
Required by the hardened compose profiles — no floating tag is assumed. Point these at an immutable digest of a reviewed image before running docker compose up. |
MEDIA_DOWNLOADER_AGENT_IMAGE |
knucklessg1/media-downloader@sha256:<digest> |
|
MEDIA_DOWNLOADER_OUTPUT_ROOT |
/data/media |
Every download is written beneath this root; a path that escapes it is rejected. Falls back to WORKSPACE_PATH, then ~/Downloads. |
WORKSPACE_PATH |
/workspace |
|
MEDIA_DOWNLOADER_ALLOW_PRIVATE_HOSTS |
media.internal.example |
Exact hostnames allowed to resolve to a private address. Downloads are restricted to publicly routable hosts otherwise; no wildcards are accepted. |
MEDIA_DOWNLOADER_MAX_WORKERS |
4 |
Parallel download workers, clamped to 1-4. |
Inherited agent-connector-sdk variables (apply to every connector)
| Variable | Example | Description |
|---|---|---|
MCP_TOOL_MODE |
intent |
Tool surface: intent | condensed | verbose | both |
MCP_ENABLED_TOOLS |
— | Comma-separated tool allow-list |
MCP_DISABLED_TOOLS |
— | Comma-separated tool deny-list |
MCP_ENABLED_TAGS |
— | Comma-separated tag allow-list |
MCP_DISABLED_TAGS |
— | Comma-separated tag deny-list |
MCP_CLIENT_AUTH |
— | Outbound MCP child auth: oidc-client-credentials | basic | none |
OIDC_CLIENT_ID |
— | OIDC client id (service-account auth) |
OIDC_CLIENT_SECRET_REF |
secret://identity/oidc-client-secret |
Runtime secret reference for the OIDC service account |
MCP_BASIC_AUTH_USERNAME |
— | HTTP Basic username (MCP_CLIENT_AUTH=basic) |
MCP_BASIC_AUTH_PASSWORD_REF |
secret://identity/mcp-basic-password |
Runtime secret reference for HTTP Basic auth (MCP_CLIENT_AUTH=basic) |
DEBUG |
False |
Verbose logging |
PYTHONUNBUFFERED |
1 |
Unbuffered stdout (recommended in containers) |
MCP_URL |
http://localhost:8000/mcp |
URL of the MCP server the agent connects to |
PROVIDER |
— | Operator-configured LLM provider for the agent |
MODEL_ID |
— | Operator-configured model id for the agent |
ENABLE_WEB_UI |
True |
Serve the AG-UI web interface |
17 package + 16 inherited variable(s). Auto-generated from .env.example + the shared agent-connector-sdk set — do not edit.
Every variable the server reads. A local template is supplied inside
.env.example — copy it to .env and adjust as needed.
MCP server / transport
| Variable | Description | Default |
|---|---|---|
TRANSPORT |
stdio, streamable-http, or sse |
stdio |
HOST |
Bind host (HTTP transports) | 0.0.0.0 |
PORT |
Bind port (HTTP transports) | 8000 |
MCP_TOOL_MODE |
Tool surface: condensed, verbose, or both |
condensed |
MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS |
Comma-separated tool allow/deny list | — |
MCP_ENABLED_TAGS / MCP_DISABLED_TAGS |
Comma-separated tag allow/deny list | — |
PYTHONUNBUFFERED |
Unbuffered stdout (recommended in containers) | 1 |
Telemetry & governance
| Variable | Description | Default |
|---|---|---|
ENABLE_OTEL |
Enable OpenTelemetry export | True |
OTEL_EXPORTER_OTLP_ENDPOINT |
OTLP collector endpoint | — |
OTEL_EXPORTER_OTLP_PUBLIC_KEY / OTEL_EXPORTER_OTLP_SECRET_KEY |
OTLP auth keys | — |
OTEL_EXPORTER_OTLP_PROTOCOL |
OTLP protocol (e.g. http/protobuf) |
— |
EUNOMIA_TYPE |
Authorization mode: none, embedded, remote |
none |
EUNOMIA_POLICY_FILE |
Embedded policy file | mcp_policies.json |
EUNOMIA_REMOTE_URL |
Remote Eunomia server URL | — |
Agent CLI (full [agent] runtime only)
| Variable | Description | Default |
|---|---|---|
MCP_URL |
URL of the MCP server the agent connects to | http://localhost:8000/mcp |
PROVIDER |
LLM provider (e.g. openai) |
openai |
MODEL_ID |
Model id (e.g. gpt-4o) |
gpt-4o |
ENABLE_WEB_UI |
Serve the AG-UI web interface | True |
Installation
Pick the extra that matches what the operator want to run:
| Extra | Installs | Use when |
|---|---|---|
media-downloader[mcp] |
Connector-focused MCP server (agent-connector-sdk — FastMCP/FastAPI + epistemic-graph[full]) |
The operator only run the MCP server (smallest install / image) |
media-downloader[all] |
Everything (mcp + agent + logfire) |
Development / both surfaces |
# Connector-focused MCP server (includes the shared graph engine)
uv pip install "media-downloader[mcp]"
# Agent runtime (adds model orchestration to the shared graph engine)
# Everything (development)
uv pip install "media-downloader[all]" # or: python -m pip install "media-downloader[all]"
Container images (:mcp)
One multi-stage docker/Dockerfile builds the MCP-only image (--target mcp):
| Image tag | Build target | Contents | Entrypoint |
|---|---|---|---|
knucklessg1/media-downloader:mcp |
--target mcp |
media-downloader[mcp] — connector-focused, includes epistemic-graph[full]; no model-orchestration stack |
media-downloader-mcp |
docker build --target mcp -t knucklessg1/media-downloader:mcp docker/ # connector-focused MCP server
agent (default build) with a co-located :mcp sidecar. For an immutable production digest, tag and
pin the operator's own build as shown in the hardened docker run pattern above.
Knowledge-graph database (epistemic-graph)
Agent Connector SDK core dependency (epistemic-graph[full]). The [mcp] extra keeps
deployments can use the bundled engine. For production — or to share one knowledge graph
across multiple agents — run epistemic-graph as its own dedicated database service and
configure the runtime to use it instead of the bundled engine. Deployment recipes
(single-node + Raft HA), connection configuration, and the full database architecture
(with diagrams) are documented in the
epistemic-graph deployment guide.
Documentation
The complete documentation is published as the official documentation site and is the recommended reference for installation, deployment, and day-to-day operation.
| Page | Contents |
|---|---|
| Installation | pip, source, extras, prebuilt Docker image |
| Deployment | run the MCP server, the agent server, Compose, Caddy + Technitium, env config |
| Usage | the MCP tools, the MediaDownloader Python API, the CLI |
| Overview | ecosystem role, enterprise readiness, architecture |
| Concepts | concept registry (CONCEPT:MDLD-*) |
AGENTS.md is the canonical contributor/agent guidance.
Repository Owners
Contribute
Contributions are welcome! Please ensure code quality by running local checks before submitting pull requests:
- Format code using
ruff format . - Lint code using
ruff check . - Validate type-safety with
mypy . - Ran test suites using
pytest
Governed capability contract
This package ships a compact canonical skill surface with specialist procedures
kept as referenced workflows. The current MCP tools, skill metadata,
connector_manifest.yml, ontology, mappings, shapes, fixtures, migrations,
tool-schema fingerprints, and certification metadata form one versioned
capability contract. Validate them together; do not rely on stale tool names or
historical per-task skill wrappers.
Runtime endpoints, credentials, certificate trust, tenant identity, retention, and observability policy are deployment inputs and are never packaged values. See Configuration, trust, and privacy before enabling a network transport, connector ingestion, Arbora delegation, or trace export.
Metadata
Release files for media-downloader 4.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| media_downloader-4.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Release files / media_downloader-4.3.1-py3-none-any.whl
| Download URL | media_downloader-4.3.1-py3-none-any.whl |
|---|---|
| Size | 81.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a94d9043a378d11d73b64614fd5d6ef3bae0ef81ff771af2de8523aea1aa038c
|
|
BLAKE2b-256 checksum How to use checksums |
05424e02555e7058be4a5abf37c6b31cfde3c37fa075a164756ccfdd14aa47b8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.4
|