How do I find my GeTui App ID and Master Secret?

Log in to the [GeTui Developer Center](https://dev.getui.com/), select your application from the dashboard, and you will find your AppID, AppKey, and MasterSecret in the application overview section.

Can I check if a specific user is currently online?

Yes. Use the `get_cid_status` tool with the user's Client ID (CID) to retrieve their current connection status to the GeTui push server.

Is it possible to list the tags for a user?

Yes! Use the `get_user_tags` tool with a Client ID to retrieve all tags associated with that user, helping you understand their segment and interests.

GeTui / 个推 MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: GeTui / 个推
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="GeTui / 个推 Specialist",
    goal="Help users interact with GeTui / 个推 effectively",
    backstory=(
        "You are an expert at leveraging GeTui / 个推 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 GeTui / 个推 "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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* 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 GeTui / 个推 MCP Server

Empower your AI agent to orchestrate your push notification infrastructure with GeTui (个推), the dominant CPaaS and developer services provider in China. By connecting GeTui to your agent, you transform complex device targeting, message broadcasting, and delivery auditing into a natural conversation. Your agent can instantly send targeted notifications to specific users, broadcast messages to your entire user base, retrieve real-time delivery and click statistics, and monitor user online status without you ever needing to navigate the comprehensive GeTui Developer Center. Whether you are automating verification flows or coordinating large-scale promotional alerts, your agent acts as a real-time messaging assistant, keeping your communication flow accurate and your user insights up-to-date.

When paired with CrewAI, GeTui / 个推 becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call GeTui / 个推 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

Push Orchestration — Send targeted, list-based, or broadcast notifications with full support for custom payloads.
User Status Monitoring — Retrieve real-time online/offline status and associate custom aliases with Client IDs (CIDs).
Tag & Interest Auditing — Browse user tags to identify audience segments and interest patterns for refined targeting.
Delivery Analytics — Access real-time statistics for push tasks, including delivery counts, display rates, and clicks.
Growth Insights — Monitor application-wide statistics for new and active users across specific dates.

The GeTui / 个推 MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect GeTui / 个推 to CrewAI via MCP

Follow these steps to integrate the GeTui / 个推 MCP Server with CrewAI.

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 10 tools from GeTui / 个推

Why Use CrewAI with the GeTui / 个推 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with GeTui / 个推 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

GeTui / 个推 + CrewAI Use Cases

Practical scenarios where CrewAI combined with the GeTui / 个推 MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries GeTui / 个推 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 GeTui / 个推, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain GeTui / 个推 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 GeTui / 个推 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

GeTui / 个推 MCP Tools for CrewAI (10)

These 10 tools become available when you connect GeTui / 个推 to CrewAI via MCP:

bind_user_alias

g., username) with a Client ID. Bind alias to user

get_app_user_stats

Get application user stats

get_cid_status

Check user online status

get_daily_push_report

Get daily push report

get_push_status

Check push task status

get_user_tags

Get user tags

push_to_all

Broadcast push to all users

push_to_list

Send push to multiple users

push_to_single

Send push to single user

query_user_alias

Query user alias

Example Prompts for GeTui / 个推 in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with GeTui / 个推 immediately.

"Send a push notification to CID '1a0918c...' with title 'Urgent Update'."

"Check the online status for user CID '9920a1b...'."

"Show me the push report for yesterday."

Troubleshooting GeTui / 个推 MCP Server with CrewAI

Common issues when connecting GeTui / 个推 to CrewAI through the 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.

GeTui / 个推 + CrewAI FAQ

Common questions about integrating GeTui / 个推 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.