How do I chat with a specific bot?

Use the `send_bot_message` tool and provide the Bot ID and your message content. The AI agent will relay your message to the GPTBots platform and return the bot's response.

Can I check the status of a triggered workflow?

Yes. When you use `trigger_workflow`, it returns a Record ID. You can then pass that Record ID to the `query_workflow` tool to monitor its execution status (e.g., Running, Success, Failed).

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

Name: GPTBots
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

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

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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 GPTBots MCP Server

Connect your GPTBots account to your AI agent and manage your enterprise AI infrastructure conversationally. Interact with your deployed bots, trigger complex automated workflows, and upload new documents to your knowledge bases without leaving your development environment.

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

Bot Interaction — List active conversations, review chat histories, and send messages directly to your deployed AI agents
Knowledge Management — Browse available knowledge documents and upload new content to keep your bots' context up to date
Workflow Automation — Trigger configured AI workflows and query their execution status programmatically
Database Queries — List tables and records hosted within the GPTBots platform database

The GPTBots 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 GPTBots to CrewAI via MCP

Follow these steps to integrate the GPTBots 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 GPTBots

Why Use CrewAI with the GPTBots MCP Server

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

GPTBots + CrewAI Use Cases

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

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

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

GPTBots MCP Tools for CrewAI (8)

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

create_knowledge_document

Upload or create a document in the Knowledge Base

get_conversation

Get details and history of a specific conversation

list_conversations

List chat conversations with a bot

list_databases

List tables in the platform database

list_knowledge_documents

List documents in a Knowledge Base

query_workflow

Check the execution status of a triggered workflow

send_bot_message

Send a message to a GPTBots Agent

trigger_workflow

Trigger an automated workflow

Example Prompts for GPTBots in CrewAI

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

"List all recent conversations for bot ID 'bot_123xyz'."

"Trigger the onboarding workflow (ID: 'wf_456') and pass the parameter email='test@example.com'."

Troubleshooting GPTBots MCP Server with CrewAI

Common issues when connecting GPTBots 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.

GPTBots + CrewAI FAQ

Common questions about integrating GPTBots 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.