Gotify MCP Server for LangChainGive LangChain instant access to 22 tools to Change Password, Create Application, Create Client, and more

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

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect Gotify 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

Open in ChatGPT Open in Claude Open in Perplexity

The Gotify MCP Server for LangChain is a standout in the Communication Messaging category — giving your AI agent 22 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

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

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({
        "gotify": {
            "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 Gotify, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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 Gotify MCP Server

Connect your Gotify instance to any AI agent to streamline your notification workflows. Gotify is a self-hosted notification server, and this MCP server allows you to interact with its API using natural language.

LangChain's ecosystem of 500+ components combines seamlessly with Gotify through native MCP adapters. Connect 22 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

Messaging — Send push notifications with custom priorities and titles, or retrieve and delete existing messages from your stream.
Application Management — Create, list, update, or delete Gotify applications to organize your notification sources and tokens.
Client Control — Manage clients and tokens to authorize different devices or services to receive messages.
User Administration — (Admin only) List or create users to manage access to your private Gotify instance.

update

Update application on Gotify

Update an application

update

Update client on Gotify

Update a client

update

Update plugin config on Gotify

Update plugin configuration

Connect Gotify to LangChain via MCP

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

Install dependencies

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

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 22 tools from Gotify via MCP

Why Use LangChain with the Gotify MCP Server

LangChain provides unique advantages when paired with Gotify through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Gotify MCP tools with 500+ LangChain components

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

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

Memory and conversation persistence let agents maintain context across Gotify queries for multi-turn workflows

Gotify + LangChain Use Cases

Practical scenarios where LangChain combined with the Gotify MCP Server delivers measurable value.

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

Autonomous research agents: LangChain agents query Gotify, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Gotify tools with web scrapers, databases, and calculators in a single agent run

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

Example Prompts for Gotify in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Gotify immediately.

"Send a high-priority Gotify message titled 'System Alert' saying 'Disk space is low on Server A'."

"List all my current Gotify applications and their descriptions."

"Get the last 5 messages from my Gotify server."

Troubleshooting Gotify MCP Server with LangChain

Common issues when connecting Gotify to LangChain through Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Gotify + LangChain FAQ

Common questions about integrating Gotify MCP Server with LangChain.

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.

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.