by binalyze
Connect to Binalyze AIR for fast digital forensics. Query endpoint data, monitor status, and manage investigations via s
Connects to Binalyze AIR digital forensics platform to manage security investigations, acquire evidence from endpoints, and monitor forensic tasks through natural language commands.
Binalyze AIR is an official MCP server published by binalyze that provides AI assistants with tools and capabilities via the Model Context Protocol. Connect to Binalyze AIR for fast digital forensics. Query endpoint data, monitor status, and manage investigations via s It is categorized under auth security, analytics data.
You can install Binalyze AIR in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Binalyze AIR is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, Binalyze AIR benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Binalyze AIR has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Binalyze AIR surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Useful MCP listing: Binalyze AIR is the kind of server we cite when onboarding engineers to host + tool permissions.
We wired Binalyze AIR into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Binalyze AIR is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Binalyze AIR is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Binalyze AIR against two servers with overlapping tools; this profile had the clearer scope statement.
Binalyze AIR reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Binalyze AIR is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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A Node.js server implementing Model Context Protocol (MCP) for Binalyze AIR, enabling natural language interaction with AIR's digital forensics and incident response capabilities.
This MCP server creates a bridge between Large Language Models (LLMs) and Binalyze AIR, allowing interaction through natural language. Retrieve information about your digital forensics environment without writing code or learning complex APIs.
Important: An API token is required for authentication. Set it using the
AIR_API_TOKENenvironment variable.
# Clone the repository
git clone https://github.com/binalyze/air-mcp
# Change to the project directory
cd air-mcp
# Install dependencies
npm install
# Build the project
npm run build
Add the following configuration to your Claude Desktop config file:
{
"mcpServers": {
"air-mcp": {
"command": "npx",
"args": ["-y", "@binalyze/air-mcp"],
"env": {
"AIR_HOST": "your-api-host.com",
"AIR_API_TOKEN": "your-api-token"
}
}
}
}
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.