rtorrent-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@rtorrent-mcpsearch for the latest episode of One Piece on Nyaa"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
rTorrent MCP Server
📖 Installation Guide — quick start, manual setup, and troubleshooting
rTorrent MCP FastMCP 3.1.0 server for anime BitTorrent automation with Austrian legal context, talking to rTorrent over XML-RPC/SCGI (not a generic site scraper).
What this is: A BitTorrent control plane: add/list/pause torrents, search indexers (Nyaa, etc.), workflows, and post-processing against your rTorrent instance. It is not a generic systems MCP, and it is not a qBittorrent Web API client.
Web UI (web_sota/): A small Vite + React dashboard + REST bridge (/api/*) on the same uvicorn process as MCP (status, torrent list, magnet add). It is a deliberately minimal alternative to the ruTorrent WebUI bundled with Dockersee Quick Start (subsection ruTorrent vs this projects webapp) and web_sota/README.md. Agents still use MCP tools for full workflows.
cd rtorrent-mcp
just
This opens an interactive dashboard showing all available commands. Run `just bootstrap` to install dependencies, then `just serve` or `just dev` to start.
### Manual Setup
If you don't have `just` installed:
### Prerequisites
- Python 3.10 or higher
- Docker Desktop (for rTorrent) - **Recommended**
- Claude Desktop (for MCP integration)
### rTorrent stack (Docker, recommended)
#### What [crazy-max/docker-rtorrent-rutorrent](https://github.com/crazy-max/docker-rtorrent-rutorrent) is
**CrazyMax** maintains a well-used Docker setup that packages **rTorrent** (the actual client), **ruTorrent** (a PHP web UI on top of rTorrent), and **nginx** as a front door. Nginx exposes **XML-RPC** on a TCP port so clients (this MCP server, scripts, other tools) can call rTorrents RPC at `/RPC2` without you wiring SCGI sockets by hand. The image is aimed at install Docker, get a working rTorrent + classic WebUI, not at building rTorrent from source.
This repos root [`docker-compose.yml`](docker-compose.yml) pins **`crazymax/rtorrent-rutorrent:latest`**, maps **XML-RPC** to **12224** and **ruTorrent** to **12222**, and uses volumes under `./config`, your downloads folder, `./watch`, and `./logs` (see the compose file for exact bind paths on Windows).
#### Install (minimal)
1. Install **Docker Desktop** and ensure it is running.
2. Clone this repository (or copy `docker-compose.yml` and related layout).
3. From the **repository root**:
docker compose up -d
(Use `docker-compose up -d` if your Docker install only provides the hyphenated CLI.)
4. Check the container:
docker logs rtorrent-mcp
5. **Endpoints (defaults in this repo):**
- **XML-RPC (for MCP):** `http://localhost:12224/RPC2`
- **ruTorrent WebUI:** `http://localhost:12222`
Point the MCP server at the RPC endpoint with **`RTORRENT_HOST`** / **`RTORRENT_PORT`** (see [docs/RTORRENT_REFERENCE.md](docs/RTORRENT_REFERENCE.md)).
#### ruTorrent vs this projects webapp (`web_sota/`)
**ruTorrent** (bundled in CrazyMaxs image) is the full UI: plugins, RSS, autotools, labels, and a lot of surface area. Many people find it **overcomplicated** and the UI **dated**; it is still the right place when you need **plugin workflows** (RSS rules, auto-move, unpack, etc.) that we do not replicate.
**Our webapp** under [`web_sota/`](web_sota/) is intentionally **rudimentary**: a small **Vite + React** dashboard on a **REST bridge** (`/api/*`) served by the same Python process as MCPsee [`web_sota/README.md`](web_sota/README.md). Today it is a **light substitute** for day-to-day glances: health, rTorrent probe, torrent list, **magnet add**. It is **not** a feature-complete ruTorrent replacement. Use it when you want something simple; keep ruTorrent (or MCP tools) when you need depth.
Run the stack (backend + Vite) with:
.\web_sota\start.ps1
Default dev URLs are documented in `web_sota/README.md` (Vite + uvicorn ports).
#### Optional: ruTorrent plugins (CrazyMax image)
The upstream image ships ruTorrent with many plugins; common automation-related ones include RSS/feeds, autotools, scheduler, unpack, ratio/seedingtime. See [docs/RTORRENT_SETUP.md](docs/RTORRENT_SETUP.md) for a longer list and configuration notes.
## Installation
**rTorrent in Docker (CrazyMax image), ports, and webapp vs ruTorrent** are covered under **[Quick Start rTorrent stack (Docker, recommended)](#rtorrent-stack-docker-recommended)** above. This section is for the **Python MCP package** and optional **desktop** wiring.
### Prerequisites
- [uv](https://docs.astral.sh/uv/) installed (RECOMMENDED)
- Python 3.12+
### Quick Start
Run immediately via `uvx`:
```bash
uvx rtorrent-mcpClaude Desktop Integration
Add to your claude_desktop_config.json:
"mcpServers": {
"rtorrent-mcp": {
"command": "uv",
"args": ["--directory", "D:/Dev/repos/rtorrent-mcp", "run", "rtorrent-mcp"]
}
}Platform setup
Quick Setup (Windows - Docker Recommended)
Prerequisites: Docker Desktop must be installed and running.
# Download the project files
# Place docker-compose.yml and install.bat in your desired directory
# Run the installation script
install.bat
# The script will:
# - Create necessary directories
# - Configure rTorrent with SCGI support
# - Start the Docker containers
# - Test the connectionManagement Commands:
start.bat # Start rTorrent containers
stop.bat # Stop rTorrent containers
status.bat # Check container status and health
uninstall.bat # Remove everythingAlternative: WSL2 Setup
# Enable WSL2 (run as Administrator)
wsl --install -d Ubuntu
# Inside WSL2 Ubuntu
sudo apt update
sudo apt install rtorrentLinux/macOS Setup
# Ubuntu/Debian
sudo apt update
sudo apt install rtorrent
# CentOS/RHEL/Fedora
sudo yum install rtorrent
# or
sudo dnf install rtorrent
# macOS
brew install rtorrent
# Verify SCGI support
rtorrent -h | grep -i scgiBasic Configuration
For Docker (Windows):
Create rTorrent configuration
# Create config directory mkdir C:\rtorrent-mcp\config # Create rtorrent.rc configuration @" # SCGI configuration for MCP server scgi_port = 0.0.0.0:5000 # Basic settings session.path.set = /config/session directory.default.set = /downloads log.execute = /config/rtorrent.log # Performance settings max_uploads.set = 50 max_connections.set = 200 max_peers.set = 100 # Austrian Legal Compliance system.method.set_key = event.download.inserted_new, anime_category, "d.custom1.set=anime" "@ | Out-File -FilePath "C:\rtorrent-mcp\config\rtorrent.rc" -Encoding UTF8Restart container to apply configuration
docker-compose restartVerify connection
# Test SCGI connection from Windows Invoke-RestMethod -Uri "http://localhost:5000/RPC2" -Method POST -ContentType "text/xml" -Body '<?xml version="1.0"?><methodCall><methodName>system.listMethods</methodName></methodCall>'
For WSL2/Linux/macOS:
Create rTorrent configuration
mkdir -p ~/.rtorrent cat > ~/.rtorrent.rc << 'EOF' # SCGI configuration for MCP server scgi_port = localhost:5000 # Basic settings session.path.set = ~/.rtorrent/session directory.default.set = ~/Downloads log.execute = ~/.rtorrent/rtorrent.log # Performance settings max_uploads.set = 50 max_connections.set = 200 max_peers.set = 100 EOFStart rTorrent daemon
# Start in background rtorrent -d # Or with systemd (create service) sudo systemctl start rtorrent sudo systemctl enable rtorrentVerify connection
# Test SCGI connection curl -X POST -H "Content-Type: text/xml" \ -d '<?xml version="1.0"?><methodCall><methodName>system.listMethods</methodName></methodCall>' \ http://localhost:5000/RPC2
For Windows, macOS, Docker, and advanced configuration options, see docs/RTORRENT_SETUP.md.
Configuration
Create a
.envfile (or set environment variables)# rTorrent settings RTORRENT_HOST=localhost RTORRENT_PORT=12224 RTORRENT_PATH=/var/lib/rtorrent/session # Nyaa.si settings NYAA_BASE_URL=https://nyaa.si # Application settings DEBUG=false LOG_LEVEL=INFO
Running the Server
# Run with stdio transport (for Claude Desktop)
python -m rtorrent_mcp.server --transport stdio
# Or with HTTP transport
python -m rtorrent_mcp.server --transport http
# Custom config file
python -m rtorrent_mcp.server --config /path/to/config.env
# Direct module execution
python src/rtorrent_mcp/server.pyDevelopment
Testing
# Run all tests
uv run pytest
# Run with coverage report
uv run pytest --cov=rtorrent_mcp --cov-report=htmlCode Style
# Format code with ruff
uv run ruff format .
# Lint code with ruff
uv run ruff check . --fix
# Type checking with pyright
uv run pyright
# Security scanning
uv run bandit -r src/
uv run safety scanRelated MCP server: rutorrent-mcp
Features in Detail
Smart Anime Search
# Basic search
await search_anime("Detective Conan", resolution="720p", group="ASW")
# Advanced search with filters
await search_anime(
query="One Piece",
resolution="1080p",
group="Erai-raws"
)rTorrent Integration
# Add torrent from magnet link
magnet = "magnet:?xt=urn:btih:..."
await add_torrent(magnet, category="anime")
# Monitor and manage downloads
await list_torrents()
await pause_torrent("torrent_hash")
await resume_torrent("torrent_hash")
await delete_torrent("torrent_hash", delete_files=True)
# Check connection status
await get_status()(AT) Austrian Legal Compliance
# Check if content is safe for Austria
is_safe = await check_austrian_legal_status(torrent_info)
if is_safe:
await add_torrent(torrent_info["magnet"])
else:
logger.warning("Content may not be legal in Austria")Extended Search Capabilities
# Search manga
await search_manga("One Piece", subcategory="translated")
# Search Japanese TV shows
await search_japanese_tv("Terrace House", subcategory="translated")
# Search movies on YTS
await search_movies("The Matrix", quality="1080p", sort_by="seeds")
# Search ebooks on Anna's Archive (60M+ books!)
await search_ebooks_annas("Python Programming", content_type="books")
# Search comics on Pirate Bay
await search_comics("Watchmen", max_results=20)Metadata Services
# Get IMDb metadata for a movie
await get_imdb_metadata("The Matrix", year=1999)
# Search IMDb for multiple matches
await search_imdb("Matrix", year=1999)
# Get TVDB metadata (requires API subscription)
await get_tvdb_metadata("Breaking Bad", year=2008)
# Get detailed Anna's Archive torrent info
await get_annas_detail("https://annas-archive.org/...")Post-Processing System
# Check for completed downloads
completed = await check_completed_downloads()
# Process a completed download
await process_completed_download("torrent_hash")
# Start automatic post-processing (background polling)
await start_post_processing()
# Stop post-processing
await stop_post_processing()
# Normalize a filename
normalized = await normalize_filename("Show.Name.S01E01.RELEASE-GROUP.mkv", category="tv")Natural Language Processing
# English commands
await sandra_anime_command("get me this weeks asw anime, 720p")
# German commands
await sandra_anime_command("lade detective conan asw 720p")
# Parse commands without executing
await parse_anime_command("asw attack on titan 1080p")
# Get command help
await get_command_help()System Tools
# Server help / tool listing
await help()
# System status and health check
await get_system_status()
# Analyze the repository
await analyze_repo()Configuration Options
Environment Variables
Variable | Default | Description |
|
| rTorrent SCGI host |
|
| rTorrent XML-RPC port |
|
| rTorrent session path |
|
| Nyaa.si base URL |
|
| Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL) |
|
| Enable debug mode |
|
| Allowed content categories |
|
| Allowed video resolutions |
|
| Maximum allowed torrent size in GB |
|
| Enable automatic post-processing |
|
| Seconds between polling for completed downloads |
|
| Remove torrent after completion |
|
| Normalize filenames before moving |
| - | Path to temporary ingestion folder for anime |
| - | Path to temporary ingestion folder for TV shows |
| - | Path to temporary ingestion folder for movies |
| - | OMDb API key for IMDb metadata (free at omdbapi.com) |
| - | TVDB API key for TV metadata (requires subscription) |
| - | Bearer/X-API-Key auth for REST API (optional, set to enable) |
|
| ASW user page on nyaa.si for direct lookup |
|
| The Pirate Bay domain (changes frequently) |
|
| OpenAI-compatible LLM endpoint (Ollama default) |
|
| LLM model for agentic workflow |
| - | Set to |
| - | Plex server URL (enables library refresh after post-process) |
| - | Plex authentication token |
| - | Jellyfin server URL (enables library scan after post-process) |
| - | Jellyfin API key |
Media Service Integration
Architecture
Two paths, depending on whether *arr is in the loop:
Direct (anime via nyaa — no *arr)
rTorrent (rtorrent-mcp initiated)
→ PostProcessor (normalize + move to ingestion)
→ MediaIntegrator (scan Plex/Jellyfin)For content downloaded directly through rtorrent-mcp (anime, manga from nyaa), the MediaIntegrator fires Plex/Jellyfin scans so files appear in your media libraries without waiting for a scheduled scan.
*arr-managed (movies/TV)
*arr (searches, decides what to grab)
→ *arr sends magnet/torrent to rTorrent (via Download Client config)
→ rTorrent downloads
→ *arr polls rTorrent' or watches folder
→ *arr imports + renames
→ *arr notifies Plex/JellyfinFor *arr-managed content, configure rTorrent as a download client directly in Radarr/Sonarr (Settings > Download Clients > rTorrent). The *arr handles everything: dispatch, completion detection, import, and media server notification. No rtorrent-mcp integration needed.
Enable Plex/Jellyfin scanning
Set the URL + API key in .env:
# Plex
PLEX_URL=http://localhost:32400
PLEX_TOKEN=your_plex_token
# Jellyfin
JELLYFIN_URL=http://localhost:8096
JELLYFIN_API_KEY=your_jellyfin_keyOnly services with both URL and key set are contacted — others are skipped silently.
Manual trigger
await torrent_management(action="notify_media", torrent_hash="...", category="tv")This fires the scan pipeline for an already-processed torrent without re-running the file move.
Documentation
API Reference
For detailed API documentation, run the server and visit:
http://localhost:10910/api/healthREST endpoints on port 10910 (same process as MCP /mcp):
GET /api/health— liveness + versionGET /api/capabilities— tools/resources/skills surface (dynamic discovery)GET /api/skills/GET /api/skills/{name}— bundled SKILL.md listing/contentGET /api/llm/discover— probe Ollama :11434 / LM Studio :1234 / vLLM :8000POST /api/ai/chat— chat completion via the configured sampling endpointGET /api/rtorrent/status/GET /api/rtorrent/torrents/POST /api/rtorrent/magnetGET /api/fleet/apps— probe the fleet webapp reservoir for live peersGET /api/v1/diagnostics/GET /api/v1/system/info— CUA smoke diagnostics
Set API_KEY in .env to require Authorization: Bearer <key> on /api/*.
Product Requirements Document
See PRD.md for product background, requirements, and technical notes.
Extended Search Guide
See EXTENDED_SEARCH_GUIDE.md for complete guide to using all search capabilities including manga, movies, ebooks, comics, and metadata services.
Post-Processing Setup
See POST_PROCESSING_SETUP.md for complete post-processing configuration guide, including ingestion folder setup and Plex integration.
Status Report
See STATUS_REPORT.md for current project status, metrics, and development roadmap.
Development
Clone this repository and
cdinto it (or open an existing clone), then install development dependencies:git clone https://github.com/sandraschi/rtorrent-mcp.git cd rtorrent-mcp uv sync --devRun tests:
uv run pytestBuild documentation:
uv run mkdocs serveThen visit http://localhost:8001
Claude Desktop integration
The recommended mcpServers snippet is under Installation Claude Desktop Integration.
Manual MCP configuration
For advanced users or custom setups, manually configure Claude Desktop:
Location: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
Location: %APPDATA%/Claude/claude_desktop_config.json (Windows)
Location: ~/.config/Claude/claude_desktop_config.json (Linux)
Add this configuration to your claude_desktop_config.json:
{
"mcpServers": {
"rtorrent-mcp": {
"command": "python",
"args": ["-m", "rtorrent_mcp.server", "--transport", "stdio"],
"cwd": "/path/to/your/rtorrent_mcp",
"env": {
"PYTHONPATH": "/path/to/your/rtorrent_mcp/src",
"RTORRENT_HOST": "localhost",
"RTORRENT_PORT": "12224",
"NYAA_BASE_URL": "https://nyaa.si"
}
}
}
}Configuration Notes:
Replace
/path/to/your/rtorrent_mcpwith your actual repository pathAdjust environment variables as needed for your setup
The server will start automatically when Claude Desktop launches
Contributing
Fork the repository
Create a feature branch (
git checkout -b feature/-feature)Commit your changes (
git commit -m 'Add some feature')Push to the branch (
git push origin feature/-feature)Open a Pull Request
🛡️ Industrial Quality Stack
This project adheres to SOTA 14.1 industrial standards for high-fidelity agentic orchestration:
Python (Core): Ruff for linting and formatting. Zero-tolerance for
printstatements in core handlers (T201).Webapp (UI): Biome for sub-millisecond linting. Strict
noConsoleLogenforcement.Protocol Compliance: Hardened
stdout/stderrisolation to ensure crash-resistant JSON-RPC communication.Automation: Justfile recipes for all fleet operations (
just lint,just fix,just dev).Security: Automated audits via
banditandsafety.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
rTorrent - The lightweight torrent client
Nyaa.si - For the anime torrents
[FastMCP](https://FastMCP 3.1.0anthropic.com) - The MCP framework
Claude Desktop - For MCP integration
Legal compliance (examples)
await check_legal_status("austria")
await check_legal_status("germany")Interpretation of results is on you; this is not legal advice.
Release group priorities (defaults)
Heuristic ordering used by search helpers (tune in config as needed):
ASW
SubsPlease
Erai-raws
EMBER
Judas
Austrian context (AT)
Tooling includes AT-oriented legal risk hints in outputs; verify locally.
Command parsing supports English and German where implemented.
Configuration
Copy .env.example to .env and configure:
RTORRENT_HOST=localhost
RTORRENT_PORT=12224
NYAA_BASE_URL=https://nyaa.si
ALLOWED_CATEGORIES=Anime
ALLOWED_RESOLUTIONS=720p,1080p
DEFAULT_RESOLUTION=720p
PREFERRED_RELEASE_GROUP=ASW
LOG_LEVEL=INFOTesting
Run Tests
# Run all tests with coverage
pytest
# Run specific test categories
pytest -m unit # Unit tests only
pytest -m integration # Integration tests only
# Run with verbose output
pytest -v
# Generate coverage report
pytest --cov=rtorrent_mcp --cov-report=htmlTest Structure
tests/
conftest.py # Test configuration and fixtures
unit/ # Unit tests (isolated components)
test_rtorrent_client.py
integration/ # Integration tests (full workflows)
test_mcp_integration.pyPowerShell Test Runner
Windows users can use the PowerShell test runner:
# Run all tests
.\scripts\run-tests.ps1
# Run with coverage
.\scripts\run-tests.ps1 -Coverage
# Run unit tests only
.\scripts\run-tests.ps1 -UnitModern Development Commands
With UV installed, from a clone of this repo at the repository root, you can use these modern commands:
# Install all dependencies (including dev tools)
uv sync --dev
# Run linting and formatting
uv run ruff check . --fix
uv run ruff format .
# Run type checking
uv run pyright
# Run security scans
uv run bandit -r src/
uv run safety scan
# Run tests with coverage
uv run pytest --cov=src/rtorrent_mcp --cov-report=html
# Build package
uv build
# Validate package
uv run twine check dist/*CI, tests, and checklist
CI: GitHub Actions runs lint, type check, and tests (see
.github/workflows/)Tests:
uv run pytest(coverage optional viapytest --cov)Self-review:
docs/MCP_PRODUCTION_CHECKLIST.mdis a checklist for hardening; it is not a third-party certification.
Treat this project like any other self-hosted tool: verify behaviour in your environment and keep dependencies updated.
Legal Disclaimer
This tool is designed for Austrian legal context where personal downloading is generally tolerated. Users in other jurisdictions should research local copyright laws. High-risk countries (Germany, Japan) require additional precautions.
Dependencies
FastMCP 3.1.0+: MCP server framework with stdio transport
UV: Modern Python package manager for fast, reliable builds
aiohttp: Async HTTP client for indexer APIs
beautifulsoup4: HTML parsing for search results
xmlrpc.client: rTorrent SCGI communication (Python stdlib)
psutil: System monitoring and health checks
pydantic: Data validation and settings management
python-dotenv: Environment configuration
Development Dependencies
ruff: Fast Python linter and formatter
pyright: Type checking and static analysis
bandit: Security vulnerability scanner
safety: Dependency vulnerability scanner
pytest: Testing framework with coverage
build & twine: Package building and publishing
Author
Maintainer: sandraschi / rtorrent-mcp contributors.
Available Tools
7 toolsagentic_rtorrent_workflowB
RTORRENT_AGENTIC_WORKFLOW — Multi-step torrent/search automation via sampling with tools.
PORTMANTEAU PATTERN RATIONALE: One entry point for LLM-orchestrated flows (search, add, legal check) without hard-coding sequences in the client.
| Name | Required | Description | Default |
|---|---|---|---|
| max_iterations | No | Max LLM rounds (default 8). | |
| available_tools | Yes | Tool names the LLM may call (e.g. torrent_management, search_management). | |
| workflow_prompt | Yes | What to accomplish in natural language (e.g. search Nyaa and add best match). |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for disclosing behavior. It mentions 'sampling with tools' but does not describe execution semantics, safety profile, side effects, costs, or the iterative loop controlled by max_iterations. This is a significant gap for an orchestration tool that may invoke multiple underlying tools.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the core purpose. The 'PORTMANTEAU PATTERN RATIONALE' header is somewhat jargon-heavy, but it justifies the design choice in a single sentence. Every sentence adds some value, and it is not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This tool is complex, orchestrating multi-step LLM-driven automation with potential for expensive or iterative operations. The description gives a high-level purpose but omits operational details like iteration limits, error behavior, or warnings about tool invocation. While an output schema exists and return values need not be explained, the description is insufficient for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover 100% of the 3 parameters (workflow_prompt, available_tools, max_iterations) with clear explanations. The tool description adds no additional parameter-specific insight beyond what the schema already provides, so a baseline score of 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'Multi-step torrent/search automation via sampling with tools' and explains it serves as a single entry point for LLM-orchestrated flows (search, add, legal check). This distinguishes it from sibling management tools, which handle single operations. The phrase 'via sampling' is slightly ambiguous but the overall purpose is specific and distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for multi-step flows via 'One entry point for LLM-orchestrated flows... without hard-coding sequences in the client.' This contrasts with hard-coding sequences and suggests using this tool when orchestration is needed, but it does not explicitly state when NOT to use it or name sibling tools as alternatives for single steps. It provides context but lacks clear exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
legal_managementA
Comprehensive legal management portmanteau tool for Austrian copyright compliance.
PORTMANTEAU PATTERN RATIONALE: Instead of creating 4+ separate tools (one per operation), this tool consolidates related legal compliance operations into a single interface. Prevents tool explosion (4 tools → 1 tool) while maintaining full functionality and improving discoverability. Follows FastMCP 2.12+ best practices.
AUSTRIAN LEGAL CONTEXT (AT):
Sandra's Location: Vienna, 9th district
Personal downloading: Generally tolerated in Austria
Anime content: Low risk for personal consumption
Commercial use: NOT supported (high risk)
Germany/Japan: High risk, VPN mandatory
RISK LEVELS:
LOW: Safe for personal use (anime, manga for personal library)
MEDIUM: Caution advised (newly released content)
HIGH: VPN recommended (commercial content, high-profile releases)
CRITICAL: Not recommended (recent theatrical releases, games)
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | The legal operation to perform. Must be one of: - "risk": Assess legal risk for content (optional: torrent_info, content_type) - "check": Check if content type is legal in Austria (requires: content_type) - "advice": Get legal advice for activity/country (optional: country, activity) - "status": Get current legal status overview (no params required) | |
| country | No | Country for legal assessment. Default: "austria". Valid: "austria", "germany", "japan", "usa", etc. | austria |
| activity | No | Activity type for legal advice. Default: "personal_download" Valid: "personal_download", "seeding", "sharing", "commercial" | personal_download |
| content_type | No | Type of content being assessed. Required for: check. Optional for: risk Valid: "anime", "manga", "movies", "tv", "ebooks", "software", "games" | |
| torrent_info | No | Torrent details for risk assessment. Optional for: risk Should include: name, size, category, seeders |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains legal context and risk categories but does not describe the tool's runtime behavior (e.g., side effects, limits of advice, how results are returned). The schema covers per-action semantics, but the description adds only domain background.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized with clear sections and a front-loaded main purpose. It is somewhat lengthy, but every section earns its place by providing necessary legal context; the structure aids scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description offers deep legal context and risk-level definitions, making it suitable for a complex legal tool. It doesn't explain return values, but an output schema is present, so that is covered. It's thorough but could be slightly more explicit about tool limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description's legal context and risk levels add meaning beyond the schema by helping interpret how parameters like content_type and country affect risk assessment, thus enriching parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for 'Austrian copyright compliance' and describes it as a 'portmanteau' consolidating legal operations. However, it doesn't explicitly differentiate from sibling tools beyond the name and general focus; the distinction is implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides extensive legal context and risk levels, implying when to use the tool (e.g., personal downloads in Austria). It does not explicitly state when not to use it or name alternative tools, leaving the 'when vs alternatives' guidance to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nlp_managementB
Comprehensive NLP management portmanteau tool for natural language anime commands.
PORTMANTEAU PATTERN RATIONALE: Instead of creating 3+ separate tools (one per operation), this tool consolidates related NLP operations into a single interface. Prevents tool explosion (3 tools → 1 tool) while maintaining full functionality and improving discoverability. Follows FastMCP 2.12+ best practices.
LANGUAGE SUPPORT:
English: "get me this weeks asw anime, 720p"
German: "lade detective conan asw 720p"
Auto-detection enabled by default
COMMAND PATTERNS:
"[get/download/lade] [anime name] [group] [resolution]"
"asw [anime name] [resolution]"
"this weeks anime [group] [resolution]"
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | Natural language command text. Required for: command, parse Examples: - "get me this weeks asw anime, 720p" - "lade detective conan asw 720p" - "download one piece subsplease 1080p" | |
| action | Yes | The NLP operation to perform. Must be one of: - "command": Execute natural language command (requires: text) - "parse": Parse command without execution (requires: text) - "help": Get command help and examples (no params required) | |
| language | No | Language hint for parsing. Default: "auto" (auto-detect). Valid: "auto", "en", "de" | auto |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is responsible for disclosing behavioral traits. It reveals auto-detection and language support but omits what 'execute' actually does (e.g., side effects like triggering downloads), error responses, or prerequisites. This is a significant transparency gap for an execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is organized with headings but is overly verbose, including a 'portmanteau pattern rationale' that discusses design philosophy rather than operational guidance. While front-loaded with the overview, several sentences could be trimmed without losing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity, the description plus detailed schema covers most operational aspects. However, it lacks clarity on execution side effects and what outputs to expect (though output schema exists). The lack of behavioral transparency makes it incomplete for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by providing command pattern templates and examples that demonstrate how to combine text, action, and language, plus the auto-detection behavior, going beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as an NLP management interface for anime commands, distinguishing it from sibling management tools by domain. While the term 'portmanteau' is jargon, the rest clarifies the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The portmanteau rationale explicitly states that this tool consolidates what would otherwise be 3+ separate tools, guiding the agent to use this single interface for NLP operations. The command patterns and language support imply when to use it, though it doesn't name specific alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_managementA
Comprehensive search management portmanteau tool for torrents and metadata.
PORTMANTEAU PATTERN RATIONALE: Instead of creating 11+ separate tools (one per search type), this tool consolidates related search operations into a single interface. Prevents tool explosion (11 tools → 1 tool) while maintaining full functionality and improving discoverability. Follows FastMCP 2.12+ best practices.
SEARCH SOURCES:
nyaa.si: Anime, manga, Japanese TV (THE gold standard for anime)
YTS: Movies (gold standard for movie torrents)
Anna's Archive: Ebooks (60M+ books, 50M+ papers - THE gold standard!)
Pirate Bay: Comics, ebooks (fallback)
OMDb/TVDB: Metadata enrichment
| Name | Required | Description | Default |
|---|---|---|---|
| pin | No | TVDB PIN. Optional for: tvdb | |
| year | No | Release year for disambiguation. Optional for: imdb, imdb_search, tvdb | |
| group | No | Release group preference. Used by: anime. Default: "ASW" (Austrian preference). Valid: "ASW", "SubsPlease", "Erai-raws", etc. | ASW |
| limit | No | Result limit. Used by: movies. Default: 20 | |
| query | No | Search query for torrent searches. Required for: anime, manga, japanese_tv, movies, ebooks_annas, ebooks_pb, comics Example: "One Piece", "Detective Conan", "Python Programming" | |
| title | No | Title for metadata lookup. Required for: imdb, imdb_search, tvdb | |
| action | Yes | The search operation to perform. Must be one of: - "anime": Search nyaa.si (requires: query, optional: resolution, group) - "manga": Search nyaa.si (requires: query, optional: subcategory) - "japanese_tv": Search nyaa.si (requires: query, optional: subcategory) - "movies": Search YTS (requires: query, optional: quality, sort_by, limit) - "ebooks_annas": Search Anna's Archive (requires: query, optional: content_type, max_results) - "ebooks_pb": Search Pirate Bay (requires: query, optional: max_results) - "comics": Search Pirate Bay (requires: query, optional: max_results) - "annas_detail": Get Anna's detail page (requires: book_url) - "imdb": Get IMDb metadata (requires: title, optional: year, imdb_id) - "imdb_search": Search IMDb (requires: title, optional: year) - "tvdb": Get TVDB metadata (requires: title, optional: year, tvdb_id) | |
| api_key | No | API key for metadata services. Optional for: imdb, imdb_search, tvdb (uses env vars if not provided) | |
| imdb_id | No | IMDb ID for direct lookup (e.g., "tt1234567"). Optional for: imdb | |
| quality | No | Movie quality. Used by: movies. Default: "1080p". Valid: "720p", "1080p", "2160p", "3D" | 1080p |
| sort_by | No | Sort order. Used by: movies. Default: "seeds". Valid: "seeds", "peers", "year", "rating", "downloads" | seeds |
| tvdb_id | No | TVDB ID for direct lookup. Optional for: tvdb | |
| book_url | No | Anna's Archive book URL for detail retrieval. Required for: annas_detail | |
| new_only | No | ||
| resolution | No | Video resolution preference. Used by: anime. Default: "720p". Valid: "480p", "720p", "1080p", "2160p" | 720p |
| max_results | No | Maximum results. Used by: ebooks_annas, ebooks_pb, comics. Default: 20 | |
| subcategory | No | Content subcategory. Used by: manga, japanese_tv. Default: "translated". Valid: "raw", "translated", "english" | translated |
| content_type | No | Content type. Used by: ebooks_annas. Default: "books". Valid: "books", "papers" | books |
| downloaded_episodes | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention whether the tool is read-only, any rate limits, authentication requirements, or possible side effects. The description only covers scope and rationale, leaving the agent without critical safety and behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (PORTMANTEAU PATTERN RATIONALE, SEARCH SOURCES) and front-loads the purpose. While the portmanteau rationale is somewhat verbose, it is relevant to understanding the tool's design. No wasted sentences, but could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 actions, 19 parameters), the description provides a useful overview and source list, while detailed per-action requirements are supplied in the schema's action enum. The description, together with the rich schema, gives the agent enough context to select the tool and action, though it does not explicitly summarize the action list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 89%, so the schema already documents parameter meanings, requirements, and defaults. The description adds no parameter-level information, but the schema's rich detail justifies the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool is a 'Comprehensive search management portmanteau tool for torrents and metadata' and explains it consolidates 11+ search operations into one interface. This clearly identifies the verb (search), the resource (torrents and metadata), and distinguishes it from sibling tools by its search focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by branding it as the single search tool ('Prevents tool explosion (11 tools → 1 tool)') and listing search sources, but does not explicitly specify when to use it vs alternatives or when not to use it. There are no named alternative tools with explicit exclusion criteria, so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
system_managementB
Comprehensive system management portmanteau tool.
PORTMANTEAU PATTERN RATIONALE: Instead of creating 5+ separate tools (one per operation), this tool consolidates related system operations into a single interface. Prevents tool explosion (5 tools → 1 tool) while maintaining full functionality and improving discoverability. Follows FastMCP 2.12+ best practices.
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | Detail level for help/status. Default: "basic". Valid: "basic", "detailed", "expert" | basic |
| topic | No | Help topic for filtered help. Optional for: help Valid: "torrent", "search", "nlp", "legal", "all" | |
| action | Yes | The system operation to perform. Must be one of: - "help": Get help documentation (optional: topic, level) - "status": Get quick system status (no params required) - "health": Detailed health check with metrics (no params required) - "info": Get server info and configuration (no params required) - "analyze": Analyze repository structure (no params required) |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description only discusses the design rationale (portmanteau pattern) and does not reveal what the operations actually do, whether they are read-only, require authentication, or have side effects. Behavioral details are relegated to the schema's action descriptions, leaving the description itself uninformative about tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with a clear summary sentence, followed by a rationale for the portmanteau pattern. The rationale adds context but is somewhat verbose for a tool description, preventing a perfect score. Overall, it is concise and well-structured, with no major fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The input schema is detailed and an output schema exists, so the description does not need to explain return values. However, the description lacks explicit usage scenarios and behavioral summaries, making it only minimally complete for an agent deciding when and how to invoke the tool. The schema compensates for parameter and action details, but the description itself leaves gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter (action, level, topic) having detailed descriptions, defaults, and valid values. The description adds no additional parameter semantics beyond what the schema already provides. Since the schema fully documents parameters, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the tool as a comprehensive system management interface that consolidates operations, clearly distinguishing it from domain-specific sibling tools (torrent, search, nlp, legal, workflow). However, it does not enumerate the specific actions, leaving the actual verbs (help, status, health, info, analyze) to the schema. This is clear in scope and domain but not fully explicit about exact operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that the tool consolidates multiple system operations into one interface, implying it should be used for system management tasks instead of separate tools. However, it provides no explicit 'when to use' vs alternatives, no exclusions, and no guidance on choosing between this and sibling tools. The usage context is implied rather than clearly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
torrent_managementC
Comprehensive torrent management portmanteau tool for rTorrent and post-processing.
PORTMANTEAU PATTERN RATIONALE: Instead of creating 12 separate tools, this tool consolidates all torrent and post-processing operations into a single interface. Prevents tool explosion while maintaining full functionality.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | The operation to perform. Must be one of: TORRENT OPERATIONS: - "add": Add torrent via magnet link (requires: magnet_link, optional: category) - "list": List all torrents with status (no params required) - "pause": Pause a torrent (requires: torrent_hash) - "resume": Resume a torrent (requires: torrent_hash) - "delete": Delete a torrent (requires: torrent_hash, optional: delete_files) - "status": Get rTorrent connection status (no params required) - "info": Get detailed torrent info (requires: torrent_hash) POST-PROCESSING OPERATIONS: - "check_completed": Check for completed downloads ready for processing - "process": Process completed download (requires: torrent_hash) - "start_processing": Start automatic post-processing loop - "stop_processing": Stop automatic post-processing loop - "normalize": Preview filename normalization (requires: filename, optional: category) | |
| category | No | Category for categorization. Used by: add, normalize. Default: "anime" | anime |
| filename | No | Filename for normalization preview. Required for: normalize | |
| magnet_link | No | Magnet URI. Required for: add | |
| delete_files | No | Delete files when deleting torrent. Default: False | |
| torrent_hash | No | Torrent hash. Required for: pause, resume, delete, info, process |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description carries the full burden of behavioral disclosure. It does not mention side effects (e.g., delete actions remove files), permission requirements, or operational characteristics. The rationale about 'tool explosion' is irrelevant to behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but includes a meta-rationale paragraph that is not directly actionable. The first sentence delivers the purpose, but the rationale consumes space that could have been used to list operations or usage hints. It is not optimally front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, 13 action types, output schema), the description is too sparse. It lacks an overview of action categories, usage context, or relationship to sibling tools. The schema provides detail, but the description fails to synthesize the tool's overall role, making it incomplete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with detailed parameter descriptions and an action enum that specifies requirements for each operation. The description adds no additional parameter semantics, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'Comprehensive torrent management portmanteau tool for rTorrent and post-processing,' which distinguishes it from sibling tools like search_management or nlp_management. However, it does not list the specific operations, relying on the schema to enumerate them, which keeps the purpose somewhat high-level.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'PORTMANTEAU PATTERN RATIONALE' explains why the tool exists but does not mention scenarios, exclusions, or comparisons to sibling tools like agentic_rtorrent_workflow. An agent receives no contextual cues for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
workflow_managementB
Complex workflow management portmanteau tool for multi-step torrent operations.
PORTMANTEAU PATTERN RATIONALE: Consolidates "tricky" long-running workflows into a single interface. Handles operations like downloading entire anime franchises that could take days.
| Name | Required | Description | Default |
|---|---|---|---|
| group | No | Release group preference. Default: "ASW" | ASW |
| action | Yes | The workflow operation. Must be one of: - "franchise": Download entire anime franchise (requires: anime_family) - "batch_series": Batch download episode range (requires: anime_family, episode_start, episode_end) - "status": Check workflow progress (optional: workflow_id) - "cancel": Cancel workflow (requires: workflow_id) - "list": List available anime franchises - "estimate": Estimate download for franchise (requires: anime_family) - "queue": View download queue - "schedule": Schedule workflow (requires: anime_family, schedule_time) | |
| dry_run | No | Preview without downloading. Default: False | |
| rate_limit | No | Max concurrent searches per minute. Default: 5 | |
| resolution | No | Video resolution. Default: "720p" | 720p |
| episode_end | No | End episode for batch_series | |
| workflow_id | No | Workflow ID for status/cancel | |
| anime_family | No | Anime franchise name (e.g., "one piece", "naruto", "detective conan") Required for: franchise, batch_series, estimate, schedule | |
| include_ovas | No | Include OVAs. Default: True | |
| episode_start | No | Start episode for batch_series | |
| schedule_time | No | Cron-like schedule for delayed execution Format: "HH:MM" or "YYYY-MM-DD HH:MM" | |
| include_movies | No | Include movies. Default: True | |
| include_series | No | Include TV series. Default: True | |
| include_specials | No | Include specials. Default: True |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It only reveals that workflows are long-running and 'tricky', but doesn't mention potential side effects, rate limits, dry_run behavior, or whether actions are asynchronous. This is insufficient for a tool with many mutation-like actions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two short paragraphs and front-loads the primary purpose. The 'PORTMANTEAU PATTERN RATIONALE' adds context but could be integrated more smoothly; still, no words are wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (14 parameters, 8 actions) and presence of an output schema, the description provides only high-level context about long-running workflows. It doesn't explain how actions interrelate or when to use dry_run/rate_limit, relying heavily on the schema for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% parameter descriptions, including action-specific requirements and defaults, so the description doesn't need to add parameter detail. The description adds no extra semantics beyond the schema's existing thorough documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for managing complex, multi-step torrent workflows, with a concrete example of downloading entire anime franchises. While it distinguishes itself from simple torrent operations, it doesn't enumerate the specific actions covered, making it somewhat broad.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for long-running, 'tricky' workflows that could take days, but it doesn't explicitly state when to use it over sibling tools like torrent_management or agentic_rtorrent_workflow. No alternatives or exclusions are mentioned.
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. Dates show when Glama detected each change.
7 tool updates
v3.0.0- First observed
agentic_rtorrent_workflow - First observed
legal_management - First observed
nlp_management - First observed
search_management - First observed
system_management - First observed
torrent_management - First observed
workflow_management
TDQS
The tools have distinct names but their scopes heavily overlap. torrent_management, workflow_management, and agentic_rtorrent_workflow all appear to handle multi-step torrent operations, making it unclear which tool should be selected for a given task. search_management and nlp_management also blur boundaries since NLP is used for search commands.
All tool names follow a consistent underscore-separated pattern with a common suffix (management or workflow). While the suffixes vary between 'management' and 'workflow', the naming is predictable and uniform in style, with minor deviations in the agentic_rtorrent_workflow name.
The server has 7 tools, which is within a reasonable range. However, each tool is a portmanteau consolidating many operations, so the effective surface area is much larger. The count is appropriate given the deliberate design to avoid tool explosion, though it might feel slightly low for the broad scope covered.
The tools cover major domains: torrent management, search, NLP, legal compliance, system operations, and workflows. The 'comprehensive' descriptions suggest a full range of operations, but the lack of specific operation lists makes it hard to verify. There are no obvious dead ends, but the vagueness could hide gaps.
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