How do I find my TA Project APPID and Tokens?

Log in to your [ThinkingAnalytics Console](https://www.thinkingdata.cn/), go to [Project Management] -> [Project Info] to find your APPID and Data Token. The Query Secret is usually found in the [Account Management] or [API Management] section.

What is the 'distinctId'?

The `distinctId` is the unique identifier for a user in your system (e.g., a device ID or an account ID). It is used to tie events and properties to a specific individual profile in ThinkingAnalytics.

Can I perform complex data analysis through the agent?

Yes! Use the `query_events` tool with a JSON query definition. Your agent will fetch the raw or aggregated results from TA, allowing you to audit behavioral patterns using natural language reasoning over the returned data.

ThinkingData / 数数科技 MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: ThinkingData / 数数科技
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to ThinkingData / 数数科技 through Vinkius, pass the Edge URL in the `mcps` parameter and every ThinkingData / 数数科技 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="ThinkingData / 数数科技 Specialist",
    goal="Help users interact with ThinkingData / 数数科技 effectively",
    backstory=(
        "You are an expert at leveraging ThinkingData / 数数科技 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 ThinkingData / 数数科技 "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

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 ThinkingData / 数数科技 MCP Server

Empower your AI agent to orchestrate your data analytics and player insights with ThinkingData (数数科技), the premier analytics platform for the global gaming industry. By connecting ThinkingData to your agent, you transform complex event querying, user profile auditing, and cohort management into a natural conversation. Your agent can instantly retrieve project metadata, list defined events and their schemas, execute complex behavioral queries, and even ingest custom events without you ever needing to navigate the comprehensive TA Dashboard. Whether you are conducting a player retention audit or coordinating a live-ops event refresh, your agent acts as a real-time data coordinator, providing accurate results from a single, authorized source.

When paired with CrewAI, ThinkingData / 数数科技 becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call ThinkingData / 数数科技 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

Project Orchestration — Retrieve project summaries, list defined events, and discover property schemas.
Behavioral Auditing — Execute complex queries on event data to understand player behavior and conversion funnels.
User Management — Query user profile data and update properties for specific distinct IDs.
Data Ingestion — Track custom events and set user properties directly through the agent for rapid testing.
Operational Insights — List defined user cohorts, saved reports, and monitor API connectivity status.

The ThinkingData / 数数科技 MCP Server exposes 8 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 ThinkingData / 数数科技 to CrewAI via MCP

Follow these steps to integrate the ThinkingData / 数数科技 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 8 tools from ThinkingData / 数数科技

Why Use CrewAI with the ThinkingData / 数数科技 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with ThinkingData / 数数科技 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

ThinkingData / 数数科技 + CrewAI Use Cases

Practical scenarios where CrewAI combined with the ThinkingData / 数数科技 MCP Server delivers measurable value.

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

Multi-source enrichment pipelines: chain ThinkingData / 数数科技 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 ThinkingData / 数数科技 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

ThinkingData / 数数科技 MCP Tools for CrewAI (8)

These 8 tools become available when you connect ThinkingData / 数数科技 to CrewAI via MCP:

get_event_properties

Get properties for event

get_project_summary

Get project overview

list_defined_events

List project events

list_project_cohorts

List user cohorts

query_events

Execute event query

query_users

Execute user query

set_user_properties

Update user profile

track_custom_event

Track a single event

Example Prompts for ThinkingData / 数数科技 in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with ThinkingData / 数数科技 immediately.

"Show me a summary of our ThinkingData project configuration."

"List all defined events in ThinkingData."

"Check the profile for user 'USER_88210934'."

Troubleshooting ThinkingData / 数数科技 MCP Server with CrewAI

Common issues when connecting ThinkingData / 数数科技 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.

ThinkingData / 数数科技 + CrewAI FAQ

Common questions about integrating ThinkingData / 数数科技 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.