Install
$ agentstack add mcp-srozb-iris-mcp ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
👁️ DFIR-Iris MCP Server
Connect your AI agents to DFIR Iris for automated incident response.
This Model Context Protocol (MCP) server enables LLMs to managing cases, tracks evidence, and record timeline events directly within your DFIR workflow.
🚀 Quick Start
The easiest way to run this server is with uv.
1. Zero-Setup Run
If you have the repository cloned, you can run the server directly without manual virtualenv creation. The script handles its own dependencies!
# Make sure you have the repository cloned
git clone https://github.com/srozb/iris-mcp.git
cd iris-mcp
# Run directly (stdio mode)
./iris_mcp.py
# Run in HTTP mode (for Gemini/debug)
./iris_mcp.py --http
Note: Requires uv to be installed.
2. Configure Credentials
The server needs access to your DFIR Iris instance. Set these environment variables:
IRIS_API_KEY: Your API key.IRIS_HOST: URL of your instance (e.g.,https://iris.example.com).IRIS_VERIFY_SSL:trueorfalse(default:true).
You can also create a .env file in the root directory:
IRIS_API_KEY=your_key
IRIS_HOST=https://iris.example.com
3. Gemini (HTTP Mode)
To run the server in HTTP mode (listening on port 9000):
uv run iris-mcp --http
Then add it to Gemini:
gemini mcp add iris http://127.0.0.1:9000/mcp
🔌 Connect to Claude Desktop
The server uses Standard Input/Output (stdio) by default, which is what Claude Desktop expects.
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"dfir-iris": {
"command": "uv",
"args": [
"run",
"--with", "dfir-iris-client>=2.0.4",
"--with", "fastmcp>=2.13.2",
"https://raw.githubusercontent.com/srozb/iris-mcp/master/iris_mcp.py"
],
"env": {
"IRIS_API_KEY": "your_api_key",
"IRIS_HOST": "https://your-iris-instance.com"
}
}
}
}
Tip: You can point args to a local path if you prefer running from source.
✨ Features
- Case Management: Create, list, search, and update cases.
- Evidence & IOCs: Add malicious IPs, domains, and file artifacts.
- Notes & Timeline: Maintain a chronological record of the investigation.
- Tasks: manage analyst tasks.
🛠️ Development
This project uses uv for all lifecycle management.
# Run tests
uv run pytest
# Lint & Format
uv run ruff check .
uv run mypy .
License
[MIT](LICENSE)
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: srozb
- Source: srozb/iris-mcp
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.