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SmartChatAI MCP Server for CrewAIGive CrewAI instant access to 12 tools to Add Pdf To Knowledge Base, Add Text To Knowledge Base, Add Website To Knowledge Base, and more

Built by Vinkius GDPR 12 Tools Framework

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

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The SmartChatAI app connector for CrewAI is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
from crewai import Agent, Task, Crew

agent = Agent(
    role="SmartChatAI Specialist",
    goal="Help users interact with SmartChatAI effectively",
    backstory=(
        "You are an expert at leveraging SmartChatAI 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 SmartChatAI "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

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

Connect your SmartChatAI account to any AI agent to automate your intelligent chatbot orchestration and lead collection. SmartChatAI provides a premier platform for building custom AI bots, and this integration allows you to retrieve chatbot metadata, manage knowledge bases via URL or PDF, and track conversational history through natural conversation.

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

  • Chatbot Orchestration — List all managed AI bots and retrieve detailed profile metadata, including status and configuration programmatically.
  • Knowledge Base Lifecycle Management — Add new data sources (URL, PDF, Text) to your bots' knowledge base directly from the AI interface to ensure they are always informed.
  • Message & Reply Control — Send automated replies and retrieve detailed chat history to maintain high-quality customer interactions via natural language.
  • Web Scraper Automation — Trigger website scraping to ingest content into your AI models and ensure your bots have the latest information.
  • Operational Monitoring — Track system health, manage webhooks, and monitor bot activity to ensure your conversational platform is always optimized.

The SmartChatAI MCP Server exposes 12 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.

All 12 SmartChatAI tools available for CrewAI

When CrewAI connects to SmartChatAI through Vinkius, your AI agent gets direct access to every tool listed below — spanning chatbot-orchestration, knowledge-base, lead-collection, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

add_pdf_to_knowledge_base

Train bot using a PDF

add_text_to_knowledge_base

Train bot using raw text

add_website_to_knowledge_base

Train bot using a URL

check_api_health

Verify SmartChatAI API status

create_new_ai_bot

Requires a name and optional initial prompt. Provision a new AI agent

get_authenticated_user_profile

Get account profile

get_bot_chat_history

Retrieve conversation transcripts

get_chatbot_details

Get configuration for a specific bot

list_ai_chatbots

List all AI chatbots

list_configured_webhooks

List active webhooks

message_ai_chatbot

Send a message and get AI reply

scrape_domain_links

Discover and index domain links

Connect SmartChatAI to CrewAI via MCP

Follow these steps to wire SmartChatAI into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from SmartChatAI

Why Use CrewAI with the SmartChatAI MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with SmartChatAI through the Model Context Protocol.

01

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

02

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

03

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

04

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

SmartChatAI + CrewAI Use Cases

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

01

Automated multi-step research: a reconnaissance agent queries SmartChatAI for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

02

Scheduled intelligence reports: set up a crew that periodically queries SmartChatAI, analyzes trends over time, and generates executive briefings in markdown or PDF format

03

Multi-source enrichment pipelines: chain SmartChatAI tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

04

Compliance and audit automation: a compliance agent queries SmartChatAI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for SmartChatAI in CrewAI

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

01

"List all active AI bots in my SmartChatAI account."

02

"Show me all active chatbot conversations with their resolution rates and average response times."

03

"Train the chatbot with 10 new FAQ entries about our refund and return policies."

Troubleshooting SmartChatAI MCP Server with CrewAI

Common issues when connecting SmartChatAI to CrewAI through the Vinkius, and how to resolve them.

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

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.

SmartChatAI + CrewAI FAQ

Common questions about integrating SmartChatAI MCP Server with CrewAI.

01

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.
02

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.
03

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.
04

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.
05

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.