Compatible with every major AI agent and IDE
What is the Sonarr (TV) MCP Server?
Connect your Sonarr instance to any AI agent to take full control of your TV media library through natural conversation.
What you can do
- Library Management — List all series, add new shows via TVDB ID, and update monitoring status or quality profiles.
- Episode Tracking — Fetch details for specific episodes, list all episodes in a series, and manage their monitored state.
- File Control — List and delete physical episode files directly from your storage to manage disk space.
- Activity Monitoring — Access download history and current queue status to see what's downloading or stalled.
- System Health — Check Sonarr's connectivity, system status, and internal health metrics to ensure smooth operation.
How it works
- Subscribe to this server
- Enter your Sonarr URL and API Key
- Start managing your media library from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Media Enthusiasts — manage your library, check episode statuses, and clean up files without opening the web interface
- Home Lab Users — automate show tracking and monitor download health via simple chat commands
- Automation Fans — integrate your media server workflows into your daily AI assistant routines
Built-in capabilities (18)
Adds a new series to the library
Deletes an episode file from disk
Removes an item from the queue
Removes a series from the library
Returns a specific episode by its ID
Returns a specific episode file
Returns any health check warnings or errors
Access the history of grabbed and imported episodes
Returns all items in the download queue
Returns a specific series by its ID
Returns system information (version, OS, paths)
Returns all currently running commands
Returns all episode files for a series
Returns all episodes for a specific series
Returns all series in the library
g., SeriesSearch, RescanSeries, RefreshSeries). Starts a new command
Updates an episode (e.g., marking it as monitored)
Updates an existing series
Why LlamaIndex?
LlamaIndex agents combine Sonarr (TV) tool responses with indexed documents for comprehensive, grounded answers. Connect 18 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.
- —
Data-first architecture: LlamaIndex agents combine Sonarr (TV) tool responses with indexed documents for comprehensive, grounded answers
- —
Query pipeline framework lets you chain Sonarr (TV) tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Sonarr (TV), a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Sonarr (TV) tools were called, what data was returned, and how it influenced the final answer
Sonarr (TV) in LlamaIndex
Sonarr (TV) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Sonarr (TV) to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Sonarr (TV) in LlamaIndex
The Sonarr (TV) 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. All 18 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
Sonarr (TV) for LlamaIndex
Every tool call from LlamaIndex to the Sonarr (TV) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I add a new TV series to my library using this agent?
Yes! Use the add_series tool. You will need to provide the title, TVDB ID, and the root folder path where the files should be stored.
How do I check if Sonarr is running correctly or has any errors?
You can use the get_health tool to see any active health checks or get_system_status to retrieve general system information and version details.
Is it possible to see what is currently being downloaded?
Absolutely. Use the get_queue tool to list all items currently in the download queue, including their status and progress.
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 Sonarr (TV) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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