AgentIndex icon
AgentIndex
arr-mcp logo
arr-mcp
★ 82
vs
fitter logo
fitter
★ 133

arr-mcp vs fitter

arr-mcp: arr-mcp centralizes the management of popular media services like Radarr, Sonarr, and Jellyfin into a single server and endpoint, enabling cross-service diagnostics and unified control. It allows users to ask complex questions across their entire media stack and receive correlated answers, simplifying tasks from content requests to file management.; fitter: Fitter is a declarative tool that transforms any website or API into structured JSON, eliminating the need for brittle scraping scripts. It's designed for AI agents, allowing Large Language Models to author, validate, and execute data extraction pipelines locally, on demand.

01

TL;DR

arr-mcp logo
arr-mcpLLM Infra · ★ 82

Diagnose why requested media isn't appearing in your library, spanning multiple services like Seerr, Radarr, and Jellyfin.

Read arr-mcp full review →
fitter logo
fitterLLM Infra · ★ 133

Scrape data from websites without APIs and enrich it with data from external APIs (e.g., GitHub trending repos scraped from HTML, then enriched via GitHub REST API).

Read fitter full review →
02

Side-by-Side Comparison

Field
arr-mcp logoarr-mcp
fitter logofitter
Category
LLM Infra
LLM Infra
Stars
★ 82
★ 133
License
MIT
MIT
Install Command
docker run -d --name arr-mcp -p 6060:6060 -v ./config:/config -e PUID=1000 -e PGID=1000 -e TZ=Europe/Amsterdam --restart unless-stopped ghcr.io/bardesss/arr-mcp:latest
go build -o fitter_mcp ./cmd/mcp && claude mcp add fitter -s user -- "$(pwd)/fitter_mcp"
Updated
2d ago
1mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Media Stack Management, Home Server Automation, API Integration
Web Scraping, Data Extraction, AI Agents
03

Features

arr-mcp logoarr-mcp
01Cross-service diagnostics for media content workflow, identifying the root cause of issues.
02Secure handling of public indexer release names, preventing malicious input in model context.
03Opt-in, previewed, and audited write operations with explicit confirmation before execution.
04Browser-based configuration UI with live diagnostics, error reporting, and audit trails.
05Unified vocabulary and interaction across twenty-four integrated tools for consistent management.
fitter logofitter
01Declarative & Auditable Configuration: AI agents produce readable, savable, and re-runnable configurations instead of throwaway code.
02Local-first Data Fetching: All data fetching occurs on the user's machine, eliminating reliance on third-party scraping APIs or per-request billing.
03Batteries Included: Provides a comprehensive set of tools including HTTP client, headless browser (Playwright/Chromium/Docker), various parsers (JSON, HTML, XML, XPath), pagination, caching, and rate-limiting.
04Multiple Usage Modes: Can be used as an MCP server for AI clients, an AI-powered CLI agent, a local CLI, an embeddable Go library, or a long-running service.
05LLM Integration via MCP: Exposes a Model Context Protocol (MCP) server, enabling Claude Code, Claude Desktop, and other MCP clients to author and run scraping pipelines.
04

Use Cases

arr-mcp logoarr-mcp
↳Diagnose why requested media isn't appearing in your library, spanning multiple services like Seerr, Radarr, and Jellyfin.
↳Monitor current downloads and identify stuck items across various download clients like SABnzbd or qBittorrent.
↳Discover un-watched content that aired recently or find new media based on specific criteria like ratings and year.
↳Perform advanced management actions, such as un-monitoring specific seasons or deleting associated files, with prior preview.
↳Identify failing indexers and understand the reasons for their failures to optimize media acquisition.
fitter logofitter
↳Scrape data from websites without APIs and enrich it with data from external APIs (e.g., GitHub trending repos scraped from HTML, then enriched via GitHub REST API).
↳Extract structured information from dynamic web pages using headless browsers for JavaScript-rendered content.
↳Automate data collection for AI agents, allowing them to dynamically generate and execute data extraction configurations based on natural language requests.
↳Generate static data sequences or transform data fields based on calculated expressions.
↳Write extracted results to local files in various formats (e.g., CSV) for reporting or further processing.
FAQ

FAQ

What is the difference between arr-mcp and fitter?
Both arr-mcp and fitter are in the LLM Infra category. arr-mcp has 82 stars, while fitter has 133 stars.
Which is better, arr-mcp or fitter?
The best choice depends on your use case. Choose arr-mcp if Diagnose why requested media isn't appearing in your library, spanning multiple services like Seerr, Radarr, and Jellyfin., and fitter if Scrape data from websites without APIs and enrich it with data from external APIs (e.g., GitHub trending repos scraped from HTML, then enriched via GitHub REST API)..
Is arr-mcp free or open source?
Yes, arr-mcp is open source on GitHub (MIT).
Is fitter free or open source?
Yes, fitter is open source on GitHub (MIT).
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