Radarr (Movies) MCP Server for LlamaIndexGive LlamaIndex instant access to 15 tools to Add Movie, Delete Movie, Delete Queue Item, and more

Name: Radarr (Movies)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Radarr (Movies) as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Radarr (Movies) MCP Server for LlamaIndex is a standout in the Content Management category — giving your AI agent 15 tools to work with, ready to go from day one.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Radarr (Movies). "
            "You have 15 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Radarr (Movies)?"
    )
    print(response)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Radarr (Movies) MCP Server

Connect your Radarr instance to any AI agent to take full control of your movie collection and PVR workflows through natural conversation.

LlamaIndex agents combine Radarr (Movies) tool responses with indexed documents for comprehensive, grounded answers. Connect 15 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Library Management — List all movies in your collection, fetch detailed metadata, and update movie configurations.
Discovery & Search — Search for new movies using TMDB integration and add them to your library with specific quality profiles.
Download Monitoring — Track your active download queue, view history of grabs/imports, and manage queue items.
System Operations — Check disk space, system status, and execute internal commands like library refreshes.
Infrastructure Mapping — Retrieve root folders and quality profiles to ensure correct organization of your media files.

The Radarr (Movies) MCP Server exposes 15 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 15 Radarr (Movies) tools available for LlamaIndex

When LlamaIndex connects to Radarr (Movies) through Vinkius, your AI agent gets direct access to every tool listed below — spanning movies, media-server, pvr, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

add

Add movie on Radarr (Movies)

Requires TMDB ID, quality profile, and root folder path. Add a new movie to Radarr

delete

Delete movie on Radarr (Movies)

Remove a movie from Radarr

delete

Delete queue item on Radarr (Movies)

Remove an item from the download queue

execute

Execute command on Radarr (Movies)

g., RescanMovie, MovieSearch, RefreshMovie, RenameMovie). Execute a specific system command

get

Get commands on Radarr (Movies)

List active or recently completed commands

get

Get disk space on Radarr (Movies)

Get disk space information

get

Get history on Radarr (Movies)

View the history of grabs and imports

get

Get movie on Radarr (Movies)

Get details for a specific movie

get

Get quality profiles on Radarr (Movies)

g., HD-1080p, Ultra-HD) configured in Radarr. Get available quality profiles

get

Get queue on Radarr (Movies)

Get the current download queue

get

Get root folders on Radarr (Movies)

Get configured root folders

get

Get system status on Radarr (Movies)

Get Radarr system status

list

List movies on Radarr (Movies)

List all movies in the Radarr library

lookup

Lookup movie on Radarr (Movies)

g., "term=Inception" or "term=tmdb:27205"). Search for movies to add to Radarr

update

Update movie on Radarr (Movies)

Provide the full movie object payload. Update an existing movie in Radarr

Connect Radarr (Movies) to LlamaIndex via MCP

Follow these steps to wire Radarr (Movies) into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 15 tools from Radarr (Movies)

Why Use LlamaIndex with the Radarr (Movies) MCP Server

LlamaIndex provides unique advantages when paired with Radarr (Movies) through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Radarr (Movies) tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Radarr (Movies) tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Radarr (Movies), a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Radarr (Movies) tools were called, what data was returned, and how it influenced the final answer

Radarr (Movies) + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Radarr (Movies) MCP Server delivers measurable value.

Hybrid search: combine Radarr (Movies) real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Radarr (Movies) to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Radarr (Movies) for fresh data

Analytical workflows: chain Radarr (Movies) queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Radarr (Movies) in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Radarr (Movies) immediately.

"List all movies currently in my Radarr library."

"Search for the movie 'Inception' and tell me its TMDB ID."

"Show me the current download queue and estimated completion times."

Troubleshooting Radarr (Movies) MCP Server with LlamaIndex

Common issues when connecting Radarr (Movies) to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Radarr (Movies) + LlamaIndex FAQ

Common questions about integrating Radarr (Movies) MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Radarr (Movies) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.