Gotify MCP Server for CrewAIGive CrewAI 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

Connect your CrewAI agents to Gotify through Vinkius, pass the Edge URL in the `mcps` parameter and every Gotify tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The Gotify MCP Server for CrewAI is a standout in the Communication Messaging category — giving your AI agent 22 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Gotify Specialist",
    goal="Help users interact with Gotify effectively",
    backstory=(
        "You are an expert at leveraging Gotify tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Gotify "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 22 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, Gotify becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Gotify tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 22 tools from Gotify

Why Use CrewAI with the Gotify MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Gotify through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Gotify + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Gotify for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Gotify, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Gotify tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Gotify against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Gotify in CrewAI

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Gotify + CrewAI FAQ

Common questions about integrating Gotify MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.