How do I find my API Token and Secret?

In Mode, click on your name in the top left, go to **My Account** > **API Tokens**. There you can create and manage your API keys.

What is the Workspace slug?

The Workspace slug is the unique identifier for your organization in the Mode URL (e.g., `app.mode.com/org_name`). The `org_name` part is your workspace slug.

Can I provide parameters when running a report?

Yes! The `run_mode_report` action accepts an optional `parameters` field where you can provide a JSON string of keys and values used by the report.

Mode Analytics MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Mode Analytics
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Mode Analytics Specialist",
    goal="Help users interact with Mode Analytics effectively",
    backstory=(
        "You are an expert at leveraging Mode Analytics 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 Mode Analytics "
        "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 Mode Analytics MCP Server

Connect your Mode Analytics workspace to any AI agent and take full control of your data science and business intelligence workflows through natural conversation.

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

Workspace Oversight — List all spaces and members to maintain visibility over your analytical environment.
Report Discovery — List and retrieve detailed metadata for reports across different spaces.
Live Execution — Trigger new report runs directly through the agent, including support for custom parameters.
Query Auditing — List the underlying SQL queries for any report to understand data lineage and logic.
Definition Tracking — List calculated field definitions to ensure consistency in your metrics.

The Mode Analytics 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 Mode Analytics to CrewAI via MCP

Follow these steps to integrate the Mode Analytics 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 Mode Analytics

Why Use CrewAI with the Mode Analytics MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Mode Analytics 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

Mode Analytics + CrewAI Use Cases

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

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

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

Mode Analytics MCP Tools for CrewAI (10)

These 10 tools become available when you connect Mode Analytics to CrewAI via MCP:

get_mode_account

Get authenticated account details

get_mode_report

Get details for a specific report

get_mode_report_run

Get details for a report run

list_mode_definitions

List calculated field definitions

list_mode_members

List workspace members

list_mode_queries

List SQL queries in a report

list_mode_report_runs

List runs for a report

list_mode_reports

List reports in a space

list_mode_spaces

List Mode Analytics spaces

run_mode_report

Trigger a new run for a report

Example Prompts for Mode Analytics in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Mode Analytics immediately.

"List all reports in the 'Marketing Analytics' space."

"Run the report with token 'rep_12345' and check its latest status."

"Show me the SQL query used in the 'Churn Analysis' report."

Troubleshooting Mode Analytics MCP Server with CrewAI

Common issues when connecting Mode Analytics 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.

Mode Analytics + CrewAI FAQ

Common questions about integrating Mode Analytics 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.