Wallarm MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Wallarm 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
Vinkius supports streamable HTTP and SSE.
import 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 Wallarm. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Wallarm?"
)
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 Wallarm MCP Server
Connect your Wallarm account to any AI agent and secure your API infrastructure through natural conversation.
LlamaIndex agents combine Wallarm tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Security Attacks — Monitor and search for active security attacks detected by Wallarm, grouped by vector (SQLi, XSS, etc.)
- Granular Hits — Perform deep forensics by searching for individual malicious HTTP request hits with full payloads
- Vulnerability Management — List and triage security vulnerabilities discovered in live API traffic directly from your agent
- API Inventory — Retrieve the automatically discovered API inventory to see all exposed endpoints and methods
- Filtering Nodes — Verify the health and heartbeat status of your deployed WAF and API gateway filtering nodes
- IP Control — Audit and manage IP allowlist/denylist rules to immediately block malicious sources or allow trusted partners
- Remediation Guidance — Access comprehensive diagnostic data and CWE mappings for specific vulnerabilities
The Wallarm MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex 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 Wallarm to LlamaIndex via MCP
Follow these steps to integrate the Wallarm MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Wallarm
Why Use LlamaIndex with the Wallarm MCP Server
LlamaIndex provides unique advantages when paired with Wallarm through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Wallarm tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Wallarm tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Wallarm, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Wallarm tools were called, what data was returned, and how it influenced the final answer
Wallarm + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Wallarm MCP Server delivers measurable value.
Hybrid search: combine Wallarm real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Wallarm 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 Wallarm for fresh data
Analytical workflows: chain Wallarm queries with LlamaIndex's data connectors to build multi-source analytical reports
Wallarm MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Wallarm to LlamaIndex via MCP:
create_ip_acl_rule
list_type must be "white" or "black". Adds an IP or CIDR range to the global allowlist or denylist
get_client_info
Retrieves details about the Wallarm account, subscription, and feature status
get_discovered_api_inventory
Retrieves the API inventory automatically discovered through passive traffic analysis
get_vulnerability_details
Retrieves comprehensive diagnostic data and exploit evidence for a specific vulnerability ID
list_filtering_nodes
Lists all deployed Wallarm WAF/API gateway filtering nodes
list_ip_acl_rules
Lists configured IP allowlist and denylist rules
search_security_attacks
Searches for security attacks detected by Wallarm, grouped by vector (SQLi, XSS, etc.)
search_security_hits
Shows full request headers and payloads for blocked traffic. Searches for granular individual malicious HTTP request hits intercepted by WAF nodes
search_vulnerabilities
Lists all open security vulnerabilities discovered in live API traffic
update_vulnerability_status
Valid statuses: open, closed, falsepositive. Changes the lifecycle status of a vulnerability (e.g., mark as closed or false positive)
Example Prompts for Wallarm in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Wallarm immediately.
"List all security attacks detected in the last hour."
"Block the malicious IP address 1.2.3.4 immediately."
"What vulnerabilities are currently open in our production API?"
Troubleshooting Wallarm MCP Server with LlamaIndex
Common issues when connecting Wallarm to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpWallarm + LlamaIndex FAQ
Common questions about integrating Wallarm 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?
Connect Wallarm with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Wallarm to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.