Is the AI Firewall MCP MCP server free to use?

Yes. AI Firewall MCP is listed on AllMCPs as a free, open Model Context Protocol server you can install into Claude Desktop, Cursor, or any MCP-compatible client.

Is the AI Firewall MCP MCP server free to use?

Yes. AI Firewall MCP is listed on AllMCPs as a free, open Model Context Protocol server you can install into Claude Desktop, Cursor, or any MCP-compatible client.

AI Firewall MCP

Multi-agent LLM security layer detecting prompt injection and jailbreaks.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Manual Client & Custom JSON ConfigExpand JSON ▾

Install Config Generator

Choose your client

claude_desktop_config.json

{
  "mcpServers": {
    "ai-firewall-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "ai-firewall-mcp"
      ]
    }
  }
}

💡 Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

Documentation Overview

GitHub • PyPI • Docker Hub

<mcp-name: io.github.Akhilucky/ai-firewall-mcp>

AI Firewall — MCP Server

A multi-agent AI security layer that protects LLMs from prompt injection, jailbreaks, and policy violations. Available as an MCP server for any MCP-compatible client (Claude Desktop, Cursor, Windsurf, Cline, Roo Code, etc.).

Quick Start

pip install

Terminal

pip install ai-firewall-mcp
ai-firewall-mcp

Docker

Terminal

docker pull akhilucky/ai-firewall-mcp:latest
docker run -i akhilucky/ai-firewall-mcp:latest

Claude Desktop

Add to claude_desktop_config.json:

pip install:

config.json

{
  "mcpServers": {
    "ai-firewall": {
      "command": "pipx",
      "args": ["run", "ai-firewall-mcp"]
    }
  }
}

Docker:

config.json

{
  "mcpServers": {
    "ai-firewall": {
      "command": "docker",
      "args": ["run", "-i", "akhilucky/ai-firewall-mcp:latest"]
    }
  }
}

Cursor / Windsurf / Cline / Roo Code

Configure in your MCP settings with:

Type: stdio
Command: docker run -i akhilucky/ai-firewall-mcp:latest
Or use ai-firewall-mcp if installed via pip

MCP Tools

Tool	Description
`analyze_prompt`	Analyze a prompt for injection, jailbreaks, exfiltration, and leakage
`get_threat_breakdown`	Detailed per-signal scoring breakdown from the last analysis
`sanitize_prompt`	Clean a suspicious prompt while preserving legitimate content
`get_firewall_status`	Health check: vector DB size, model status, uptime
`benchmark_firewall`	Run the adversarial test suite and return detection statistics

Testing with MCP Inspector

Terminal

npx @modelcontextprotocol/inspector ai-firewall-mcp

Architecture

The firewall runs three agents per prompt:

Code

User Prompt → [Retrieval Agent] → [Guard Agent] → [Policy Agent] → LLM
                   │                    │               │
                   ▼                    ▼               ▼
              Vector DB (FAISS)    Threat Signals    Allow/Block

Agent	Role
Retrieval Agent	Semantic search against known attack patterns (FAISS + sentence-transformers)
Guard Agent	Multi-signal classification: vector similarity, keyword match, heuristic scoring
Policy Agent	Final decision: `ALLOW` / `BLOCK` / `SANITIZE` based on configurable thresholds

Threat signals are weighted: 40% vector similarity, 25% keyword match, 20% heuristic, 15% policy weight.

Configuration

Env Var	Default	Description
`FIREWALL_MODE`	`strict`	`strict` / `moderate` / `permissive`
`SIMILARITY_THRESHOLD`	`0.50`	Vector match threshold (lower = stricter)
`LOG_LEVEL`	`INFO`	Logging verbosity

CLI / API Usage

bash

# Interactive dashboard
python main.py

# Red-team adversarial tests
python main.py --redteam

# REST API server
python main.py --api

# Single prompt analysis
python main.py --analyze "Ignore all previous instructions"

The REST API runs at http://localhost:8000 with OpenAPI docs at /docs (requires pip install ai-firewall-mcp[api]).

Testing

bash

pytest tests/ -v          # Full test suite (43 tests)
pytest tests/test_mcp.py  # MCP-specific tests only

Project Structure

Code

├── src/ai_firewall/          # MCP server package (PyPI entry)
│   ├── mcp_server.py         #    5 MCP tools, stdio transport
│   ├── threat_scorer.py      #    Per-signal scoring breakdown
│   └── __init__.py
├── src/agents/               # Core firewall agents
├── tests/                    # Test suites
├── Dockerfile                # Docker image (2.04GB, CPU-only torch)
├── pyproject.toml            # Package config & metadata
└── .github/workflows/ci.yml  # CI/CD pipeline

License

MIT — see LICENSE.

Built for security. Designed for production.

Related MCP Servers

View all in Security View all alternatives

Frequently Asked Questions about AI Firewall MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "ai-firewall-mcp": { "command": "npx", "args": ["-y", "AI Firewall MCP"] } }

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Technical Specs & Signals

CategorySecurity

27Quality signal: Emerging · 27/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20

Documentation & tools11/30

Adoption & activity1/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

★ Featured

Moxie Docs MCP

MCP & Agent Skills for Automated Documentation, and codebase conventions + context

Explore Server →

Own this project?

This directory is pre-filled from public sources. Claim via GitHub README, site badge, or DNS TXT to get the verified badge and attach your website.

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More in 🔒 Security →Best MCP servers for Security →Alternatives to AI Firewall MCP →Install in Claude Desktop Install in Cursor Install in VS Code

AI Firewall MCP

Multi-agent LLM security layer detecting prompt injection and jailbreaks.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Manual Client & Custom JSON ConfigExpand JSON ▾

Install Config Generator

Choose your client

claude_desktop_config.json

{
  "mcpServers": {
    "ai-firewall-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "ai-firewall-mcp"
      ]
    }
  }
}

💡 Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

Documentation Overview

GitHub • PyPI • Docker Hub

<mcp-name: io.github.Akhilucky/ai-firewall-mcp>

AI Firewall — MCP Server

Quick Start

pip install

Terminal

pip install ai-firewall-mcp
ai-firewall-mcp

Docker

Terminal

docker pull akhilucky/ai-firewall-mcp:latest
docker run -i akhilucky/ai-firewall-mcp:latest

Claude Desktop

Add to claude_desktop_config.json:

pip install:

config.json

{
  "mcpServers": {
    "ai-firewall": {
      "command": "pipx",
      "args": ["run", "ai-firewall-mcp"]
    }
  }
}

Docker:

config.json

{
  "mcpServers": {
    "ai-firewall": {
      "command": "docker",
      "args": ["run", "-i", "akhilucky/ai-firewall-mcp:latest"]
    }
  }
}

Cursor / Windsurf / Cline / Roo Code

Configure in your MCP settings with:

Type: stdio
Command: docker run -i akhilucky/ai-firewall-mcp:latest
Or use ai-firewall-mcp if installed via pip

MCP Tools

Tool	Description
`analyze_prompt`	Analyze a prompt for injection, jailbreaks, exfiltration, and leakage
`get_threat_breakdown`	Detailed per-signal scoring breakdown from the last analysis
`sanitize_prompt`	Clean a suspicious prompt while preserving legitimate content
`get_firewall_status`	Health check: vector DB size, model status, uptime
`benchmark_firewall`	Run the adversarial test suite and return detection statistics

Testing with MCP Inspector

Terminal

npx @modelcontextprotocol/inspector ai-firewall-mcp

Architecture

The firewall runs three agents per prompt:

Code

User Prompt → [Retrieval Agent] → [Guard Agent] → [Policy Agent] → LLM
                   │                    │               │
                   ▼                    ▼               ▼
              Vector DB (FAISS)    Threat Signals    Allow/Block

Agent	Role
Retrieval Agent	Semantic search against known attack patterns (FAISS + sentence-transformers)
Guard Agent	Multi-signal classification: vector similarity, keyword match, heuristic scoring
Policy Agent	Final decision: `ALLOW` / `BLOCK` / `SANITIZE` based on configurable thresholds

Threat signals are weighted: 40% vector similarity, 25% keyword match, 20% heuristic, 15% policy weight.

Configuration

Env Var	Default	Description
`FIREWALL_MODE`	`strict`	`strict` / `moderate` / `permissive`
`SIMILARITY_THRESHOLD`	`0.50`	Vector match threshold (lower = stricter)
`LOG_LEVEL`	`INFO`	Logging verbosity

CLI / API Usage

bash

# Interactive dashboard
python main.py

# Red-team adversarial tests
python main.py --redteam

# REST API server
python main.py --api

# Single prompt analysis
python main.py --analyze "Ignore all previous instructions"

The REST API runs at http://localhost:8000 with OpenAPI docs at /docs (requires pip install ai-firewall-mcp[api]).

Testing

bash

pytest tests/ -v          # Full test suite (43 tests)
pytest tests/test_mcp.py  # MCP-specific tests only

Project Structure

Code

├── src/ai_firewall/          # MCP server package (PyPI entry)
│   ├── mcp_server.py         #    5 MCP tools, stdio transport
│   ├── threat_scorer.py      #    Per-signal scoring breakdown
│   └── __init__.py
├── src/agents/               # Core firewall agents
├── tests/                    # Test suites
├── Dockerfile                # Docker image (2.04GB, CPU-only torch)
├── pyproject.toml            # Package config & metadata
└── .github/workflows/ci.yml  # CI/CD pipeline

License

MIT — see LICENSE.

Built for security. Designed for production.

Related MCP Servers

View all in Security View all alternatives

Frequently Asked Questions about AI Firewall MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "ai-firewall-mcp": { "command": "npx", "args": ["-y", "AI Firewall MCP"] } }

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:

Live Dynamic SVG Preview

Markdown (GitHub README)

[![AllMCPs](https://allmcps.com/api/badge/ai-firewall-mcp?style=directory)](https://allmcps.com/mcp/ai-firewall-mcp)

HTML Embed

<a href="https://allmcps.com/mcp/ai-firewall-mcp"><img src="https://allmcps.com/api/badge/ai-firewall-mcp?style=directory" alt="AI Firewall MCP on AllMCPs" /></a>

Technical Specs & Signals

CategorySecurity

27Quality signal: Emerging · 27/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20

Documentation & tools11/30

Adoption & activity1/15

Community engagement0/10

★ Featured

Moxie Docs MCP

MCP & Agent Skills for Automated Documentation, and codebase conventions + context

Explore Server →

Own this project?

This directory is pre-filled from public sources. Claim via GitHub README, site badge, or DNS TXT to get the verified badge and attach your website.

Free dofollow backlink: after claiming, verify your product site and place a dofollow AllMCPs badge — we recheck it stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in 🔒 Security →Best MCP servers for Security →Alternatives to AI Firewall MCP →Install in Claude Desktop Install in Cursor Install in VS Code