Bring Chatbot Builder
to CrewAI
Learn how to connect ChatFly to CrewAI and start using 7 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the ChatFly MCP Server?
Connect your ChatFly account to any AI agent and take full control of your custom chatbot orchestration and automated knowledge ingestion workflows through natural conversation.
What you can do
- Bot Orchestration — Create and manage multiple high-fidelity AI chatbot instances programmatically, including configuring welcome messages and internal metadata
- Knowledge Ingestion — Programmatically train your bots by uploading website URLs and documents to coordinate an accurate, data-driven knowledge base
- Real-Time Interaction — Send messages and retrieve AI responses from specific bots to test performance or integrate chat into custom business applications
- Source Management — Access and monitor your complete directory of data sources (URLs, docs) to oversee the information feeding your digital assistants
- Operational Monitoring — Track chatbot performance, session histories, and account-level status directly through your agent for instant reporting
How it works
1. Subscribe to this server
2. Retrieve your API Key from your ChatFly dashboard (Account Settings > API Keys)
3. Start building and training your custom AI agents from Claude, Cursor, or any MCP client
No more manual copy-pasting of website content for training. Your AI acts as your dedicated bot engineer and knowledge architect.
Who is this for?
- Customer Support Teams — instantly update bot knowledge bases and check chat histories using natural language commands
- Developers — integrate custom-trained AI assistants into internal tools and monitor session logs without leaving your workspace
- Business Owners — automate the deployment of 24/7 support bots and verify training progress through simple AI queries
Built-in capabilities (7)
Interact with a chatbot
Provide name and welcome message. Create a new chatbot
Get details of a specific bot
List all chatbots
List data sources for a bot
Update an existing bot
Add a knowledge source to a bot
Why CrewAI?
When paired with CrewAI, ChatFly becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call ChatFly tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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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
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter 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
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
ChatFly in CrewAI
ChatFly and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect ChatFly to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for ChatFly in CrewAI
The ChatFly 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. All 7 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
ChatFly for CrewAI
Every tool call from CrewAI to the ChatFly MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find my ChatFly API Key?
Log in to your account, navigate to Account Settings > API Keys, and generate a new key for your integration.
Can I train a bot on a specific URL?
Yes! Use the upload_data_source tool and provide the bot ID along with the website URL you want the bot to learn from.
How do I test a bot's response via AI?
Use the chat tool to send a message to a specific bot ID. Your agent will return the high-fidelity AI response generated by ChatFly.
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.
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.