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Sonarr (TV) MCP Server for LangChainGive LangChain instant access to 18 tools to Add Series, Delete Episode File, Delete Queue Item, and more

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LangChain is the leading Python framework for composable LLM applications. Connect Sonarr (TV) through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this MCP Server for LangChain

The Sonarr (TV) MCP Server for LangChain is a standout in the Productivity category — giving your AI agent 18 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "sonarr-tv": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Sonarr (TV), show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Sonarr (TV)
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Sonarr (TV) MCP Server

Connect your Sonarr instance to any AI agent to take full control of your TV media library through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Sonarr (TV) through native MCP adapters. Connect 18 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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.

The Sonarr (TV) MCP Server exposes 18 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 18 Sonarr (TV) tools available for LangChain

When LangChain connects to Sonarr (TV) through Vinkius, your AI agent gets direct access to every tool listed below — spanning media-management, pvr, automation, 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 series on Sonarr (TV)

Adds a new series to the library

delete

Delete episode file on Sonarr (TV)

Deletes an episode file from disk

delete

Delete queue item on Sonarr (TV)

Removes an item from the queue

delete

Delete series on Sonarr (TV)

Removes a series from the library

get

Get episode on Sonarr (TV)

Returns a specific episode by its ID

get

Get episode file on Sonarr (TV)

Returns a specific episode file

get

Get health on Sonarr (TV)

Returns any health check warnings or errors

get

Get history on Sonarr (TV)

Access the history of grabbed and imported episodes

get

Get queue on Sonarr (TV)

Returns all items in the download queue

get

Get series on Sonarr (TV)

Returns a specific series by its ID

get

Get system status on Sonarr (TV)

Returns system information (version, OS, paths)

list

List commands on Sonarr (TV)

Returns all currently running commands

list

List episode files on Sonarr (TV)

Returns all episode files for a series

list

List episodes on Sonarr (TV)

Returns all episodes for a specific series

list

List series on Sonarr (TV)

Returns all series in the library

start

Start command on Sonarr (TV)

g., SeriesSearch, RescanSeries, RefreshSeries). Starts a new command

update

Update episode on Sonarr (TV)

Updates an episode (e.g., marking it as monitored)

update

Update series on Sonarr (TV)

Updates an existing series

Connect Sonarr (TV) to LangChain via MCP

Follow these steps to wire Sonarr (TV) into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 18 tools from Sonarr (TV) via MCP

Why Use LangChain with the Sonarr (TV) MCP Server

LangChain provides unique advantages when paired with Sonarr (TV) through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine Sonarr (TV) MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Sonarr (TV) queries for multi-turn workflows

Sonarr (TV) + LangChain Use Cases

Practical scenarios where LangChain combined with the Sonarr (TV) MCP Server delivers measurable value.

01

RAG with live data: combine Sonarr (TV) tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Sonarr (TV), synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Sonarr (TV) tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Sonarr (TV) tool call, measure latency, and optimize your agent's performance

Example Prompts for Sonarr (TV) in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Sonarr (TV) immediately.

01

"List all TV series in my Sonarr library."

02

"Check the current download queue and history."

03

"Get details for episode ID 1542."

Troubleshooting Sonarr (TV) MCP Server with LangChain

Common issues when connecting Sonarr (TV) to LangChain through Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Sonarr (TV) + LangChain FAQ

Common questions about integrating Sonarr (TV) MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

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