Can I train my bot with a new URL through the agent?

Yes! Use the `add_data_source` tool and provide the Bot ID and the target URL. The bot will automatically scrape and learn from that page.

How do I review the chat history of a specific user conversation?

First, use `list_conversations` to find the active sessions. Then, use `get_conversation_history` with the Conversation ID to retrieve the full log of messages.

Does the integration allow me to create a completely new bot?

Yes. Use the `create_bot` action and provide a name and a system prompt/instructions. The bot will be instantly created in your account.

Bot9 MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Bot9
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Bot9 through the Vinkius — pass the Edge URL in the `mcps` parameter and every Bot9 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="Bot9 Specialist",
    goal="Help users interact with Bot9 effectively",
    backstory=(
        "You are an expert at leveraging Bot9 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 Bot9 "
        "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 Bot9 MCP Server

Connect your Bot9 account to any AI agent and orchestrate your customer support and conversational automation workflows through natural language.

When paired with CrewAI, Bot9 becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Bot9 tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Bot Management — List all configured AI bots, retrieve specific configurations, and create new bots on the fly.
Training & Data Sources — List existing knowledge base sources and dynamically add new URLs for your bots to learn from.
Conversation Oversight — Retrieve active conversation lists and export historical chat logs for analysis.
Message Automation — Send messages to your bots programmatically to test responses or simulate user interactions.

The Bot9 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 Bot9 to CrewAI via MCP

Follow these steps to integrate the Bot9 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 Bot9

Why Use CrewAI with the Bot9 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Bot9 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 the 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

Bot9 + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Bot9 MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Bot9 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 Bot9, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Bot9 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 Bot9 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Bot9 MCP Tools for CrewAI (8)

These 8 tools become available when you connect Bot9 to CrewAI via MCP:

add_data_source

Add a URL to train the bot

create_bot

Create a new AI chatbot

get_bot

Get details of a specific bot

get_conversation_history

Retrieve message history of a conversation

list_bots

List all AI bots

list_conversations

List active conversations for a bot

list_data_sources

List knowledge base sources for a bot

send_message

Send a message to a bot and get a response

Example Prompts for Bot9 in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Bot9 immediately.

"List all bots in my Bot9 account."

"Add the URL https://example.com/pricing to bot_123's knowledge base."

"Get the chat history for conversation conv_789 on bot_123."

Troubleshooting Bot9 MCP Server with CrewAI

Common issues when connecting Bot9 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

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

Bot9 + CrewAI FAQ

Common questions about integrating Bot9 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.