Gotify MCP Server for LlamaIndexGive LlamaIndex 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

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Gotify 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 Gotify MCP Server for LlamaIndex 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

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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 Gotify. "
            "You have 22 tools available."
        ),
    )

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

asyncio.run(main())

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Ed25519Audit chain

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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.

LlamaIndex agents combine Gotify tool responses with indexed documents for comprehensive, grounded answers. Connect 22 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

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 LlamaIndex via MCP

Follow these steps to wire Gotify 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 22 tools from Gotify

Why Use LlamaIndex with the Gotify MCP Server

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

Data-first architecture: LlamaIndex agents combine Gotify tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Gotify tool calls with transformations, filters, and re-rankers in a typed pipeline

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

Observability integrations show exactly what Gotify tools were called, what data was returned, and how it influenced the final answer

Gotify + LlamaIndex Use Cases

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

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

Data enrichment: query Gotify 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 Gotify for fresh data

Analytical workflows: chain Gotify queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Gotify in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Gotify + LlamaIndex FAQ

Common questions about integrating Gotify 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 Gotify tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.