CrowdSec MCP Server for LlamaIndexGive LlamaIndex instant access to 3 tools to Get Cti Smoke, Get Decisions, Get Decisions Stream
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add CrowdSec as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this MCP Server for LlamaIndex
The CrowdSec MCP Server for LlamaIndex is a standout in the Fort Knox category — giving your AI agent 3 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to CrowdSec. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in CrowdSec?"
)
print(response)
asyncio.run(main())
* 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 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.
LlamaIndex agents combine CrowdSec tool responses with indexed documents for comprehensive, grounded answers. Connect 3 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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.
The CrowdSec MCP Server exposes 3 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 3 CrowdSec tools available for LlamaIndex
When LlamaIndex connects to CrowdSec through Vinkius, your AI agent gets direct access to every tool listed below — spanning threat-intelligence, firewall-management, ip-reputation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Get cti smoke on CrowdSec
Get CTI reputation for an IP
Get decisions on CrowdSec
Query CrowdSec LAPI for decisions
Get decisions stream on CrowdSec
Poll for new and deleted decisions from LAPI
Connect CrowdSec to LlamaIndex via MCP
Follow these steps to wire CrowdSec into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the CrowdSec MCP Server
LlamaIndex provides unique advantages when paired with CrowdSec through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine CrowdSec tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain CrowdSec tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query CrowdSec, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what CrowdSec tools were called, what data was returned, and how it influenced the final answer
CrowdSec + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the CrowdSec MCP Server delivers measurable value.
Hybrid search: combine CrowdSec real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query CrowdSec to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying CrowdSec for fresh data
Analytical workflows: chain CrowdSec queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for CrowdSec in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with CrowdSec immediately.
"Check if there are any active decisions for IP 1.2.3.4 in our local CrowdSec database."
"Get the latest stream of decisions from CrowdSec to see recent blocks."
"What is the global reputation of IP 185.220.101.101 according to CrowdSec CTI?"
Troubleshooting CrowdSec MCP Server with LlamaIndex
Common issues when connecting CrowdSec to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCrowdSec + LlamaIndex FAQ
Common questions about integrating CrowdSec MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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