Bring Threat Intelligence
to CrewAI
Learn how to connect CrowdSec to CrewAI and start using 3 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the CrowdSec MCP Server?
Connect your CrowdSec security engine to any AI agent to take full control of your threat intelligence and network defense through natural conversation.
What you can do
- Local Decisions — Query your Local API (LAPI) for active blocks or decisions on specific IPs, ranges, or scopes to understand current local threats.
- Decision Streaming — Poll for real-time updates on new and deleted decisions from your local database to keep your security context synchronized.
- Global CTI Reputation — Fetch global IP reputation data, behaviors, and classifications from the CrowdSec Community Threat Intelligence (CTI) network.
- Security Auditing — Inspect metadata and classifications for suspicious actors directly from your command interface or code editor.
How it works
- Subscribe to this server
- Enter your CrowdSec LAPI URL, LAPI Key, and CTI Key
- Start managing your security posture from Claude, Cursor, or any MCP-compatible client
No more manual log diving or complex CLI commands to check if an IP is malicious. Your AI acts as a dedicated security analyst.
Who is this for?
- Security Engineers — instantly retrieve local decision statuses and global reputation metrics without leaving the terminal
- DevOps Teams — monitor security streams and verify IP behaviors during incident response directly from the IDE
- System Administrators — automate the auditing of blocked ranges and suspicious network activity through natural language
Built-in capabilities (3)
Get CTI reputation for an IP
Query CrowdSec LAPI for decisions
Poll for new and deleted decisions from LAPI
Why CrewAI?
When paired with CrewAI, CrowdSec becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call CrowdSec tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
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
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
CrowdSec in CrewAI
CrowdSec and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect CrowdSec 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 | 4,000+ 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 CrowdSec in CrewAI
The CrowdSec 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 3 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
CrowdSec for CrewAI
Every tool call from CrewAI to the CrowdSec MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I check if a specific IP address is currently blocked in my local CrowdSec instance?
Yes! Use the get_decisions tool providing the IP address. Your agent will query your Local API and return any active decisions, including the reason and duration of the block.
How do I see the latest security threats detected by my server in real-time?
You can use the get_decisions_stream tool. This allows your agent to poll for new and deleted decisions, giving you a clear view of recent security activity on your infrastructure.
Can I verify an IP's global reputation even if it hasn't attacked my server yet?
Absolutely. The get_cti_smoke tool queries the global CrowdSec CTI network. It provides background information, attack behaviors, and risk scores for any IP based on community data.
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.
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