Prisma AIRS MCP 安全中继 logo

Prisma AIRS MCP 安全中继

Organization
PaloAltoNetworks

Palo Alto Networks AI Runtime Security Model Context Protocol (MCP) Relay Server

PublisherPaloAltoNetworks
Repositorypan-mcp-relay
LanguagePython
Forks
8
Stars
34
Available tools
0
Transport typestdio
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  • Connect tools to AI workflows

    Prisma AIRS MCP 安全中继 exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    34 stars and 8 forks from the linked repository.

Prisma AIRS MCP Security Relay

By Palo Alto Networks

Overview

pan-mcp-relay is a security-enhanced Model Context Protocol (MCP) Relay (Proxy) Server providing real-time AI threat protection for MCP Clients, built with the Prisma AIRS AI Runtime API Intercept.

pan-mcp-relay will help protect MCP Clients such as IDE's, LLM Chat Clients, and AI Agents from harmful MCP Server Tools by automatically scanning and blocking various threats, including prompt injections, malicious URLs, insecure outputs, AI agentic threats, sensitive data loss, and more.

The MCP Relay scans all MCP Server tool descriptions, tool call parameters, and tool call responses.

For licensing, onboarding, activation, and to obtain an API authentication key and profile name, refer to the Prisma AIRS AI Runtime: API Intercept Overview administration documentation.

Prerequisites

Follow the following Activation and Onboarding guides:

  1. Create and associate a deployment profile for Prisma AIRS AI Runtime API intercept in your Customer Support Portal.
  2. Onboard Prisma AIRS AI Runtime API intercept in Strata Cloud Manager.
  3. Manage applications, API keys, security profiles, and custom topics in Strata Cloud Manager.

Requirements for Prisma AIRS API Usage

  1. API Key: Generate an API Key during the onboarding process in Strata Cloud Manager (see the onboarding prerequisite step above).
  • Specify the API Key via configuration flag, environment variable or configuration file.
  1. AI Security Profile Name: This is the API security profile you created during the onboarding process in Strata Cloud Manager (see the prerequisite step on creating an API security profile above).
  • Specify the profile name or the profile ID via configuration flag, environment variable, or configuration file.

[!NOTE] You can manage API keys and AI security profiles in Strata Cloud Manager.

  1. Log in to Strata Cloud Manager.

  2. Navigate to Insights > Prisma AIRS > Prisma AIRS AI Runtime: API Intercept.

  3. In the top right corner, click:

  • Manage > API Keys to copy, regenerate, or rotate the API key token.
  • Manage > Security Profiles to fetch details or update AI security profiles.
  • Manage > Custom Topics create or update custom topics for custom topic guardrails threat detections.

For complete details, refer to the Activation and Onboarding guides on how to Manage Applications, API Keys, Security Profiles, and Custom Topics.

Installation

We highly recommend using uv over pip or pipx. Try it! You'll love it.

See more installation methods at https://docs.astral.sh/uv/getting-started/installation/.

Standalone installer

uv provides a standalone installer to download and install uv:

=== "macOS and Linux"

Use `curl` to download the script and execute it with `sh`:

```console
$ curl -LsSf https://astral.sh/uv/install.sh | sh
```

If your system doesn't have `curl`, you can use `wget`:

```console
$ wget -qO- https://astral.sh/uv/install.sh | sh
```

Request a specific version by including it in the URL:

```console
$ curl -LsSf https://astral.sh/uv/0.8.13/install.sh | sh
```

=== "Windows"

Use `irm` to download the script and execute it with `iex`:

```pwsh-session
PS> powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```

Changing the [execution policy](https://learn.microsoft.com/en-us/powershell/module/microsoft.powershell.core/about/about_execution_policies?view=powershell-7.4#powershell-execution-policies) allows running a script from the internet.

Request a specific version by including it in the URL:

```pwsh-session
PS> powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/0.8.13/install.ps1 | iex"
```

!!! tip

The installation script may be inspected before use:

=== "macOS and Linux"

    ```console
    $ curl -LsSf https://astral.sh/uv/install.sh | less
    ```

=== "Windows"

    ```pwsh-session
    PS> powershell -c "irm https://astral.sh/uv/install.ps1 | more"
    ```

Alternatively, the installer or binaries can be downloaded directly from [GitHub](#github-releases).

Update uv if already installed - uv releases updates frequently, so make sure you're on the latest.

uv self update

Quickstart: Install and Run via pypi.org

Install and run pan-mcp-relay in one line, showing the CLI help:

sh
uvx pan-mcp-relay@latest --help

[!NOTE] While this makes it easy to get started, you can get faster startup times by following the Standard Install

Standard Install

uv installs to a standard location, which automatically added to your $PATH during uv installation.

On macOS and Linux, this is usually ~/.local/bin.

sh
# Installs to $(uv tool dir)/pan-mcp-relay
uv tool install pan-mcp-relay@latest

# Executable symlinked to $(uv tool dir --bin)/pan-mcp-relay
pan-mcp-relay --help

Install the bleeding edge development version

sh
uv tool install https://github.com/PaloAltoNetworks/aisecurity-mcp-relay.git
pan-mcp-relay --help

Upgrade

If you're using uvx pan-mcp-relay@latest, you're already using the latest version.

Update the installed version with

sh
uv tool install --upgrade pan-mcp-relay
  1. Install or Upgrade pan-mcp-relay using uv: uv tool install --upgrade pan-mcp-relay
  2. Create an mcp-relay.yaml configuration file containing:
    1. Prisma AIRS API Configuration
      • Prisma AIRS API Key
      • Prisma AIRS AI Profile
      • Prisma AIRS API Endpoint (Optional, defaults to United States Prisma AIRS API Endpoint.)
    2. MCP Servers
      • Supports stdio, SSE, and Streamable HTTP MCP Servers.
    3. Run the MCP Relay Server

Configuration

MCP Relay Server Configuration

Configuration Precedence

  1. CLI Flags
  2. Environment Variables
  3. .env file variables
  4. Configuration File

pan-mcp-relay supports loading a configuration file via --config-file flag, MCP_RELAY_CONFIG_FILE environment variable, or detecting a configuration file on a set of pre-determined locations:

  • --config-file (-c) CLI flag
  • MCP_RELAY_CONFIG_FILE environment variable
  • ./mcp-relay.yaml
  • ~/.mcp-relay.yaml
  • ~/.config/pan-mcp-relay/mcp-relay.yaml
  • ./mcp-relay.json
  • ~/.mcp-relay.json
  • ~/.config/pan-mcp-relay/mcp-relay.json

Configuration File Format

An example MCP Relay Server configuration is available in the repository in examples/config/mcp-relay.yaml

Copy or create a new mcp-relay.yaml file. The only required section is mcpServers: {}.

yaml
# mcpRelay section is optional.
# Specify API Key, AI Profile and API Endpoint via CLI flags or environment variables.
mcpRelay:
  # Prisma AIRS API Key (required), environment variables supported
  apiKey: |
    ${PRISMA_AIRS_API_KEY}
  # Prisma AIRS AI Profile Name or ID (required), environment variables supported
  aiProfile: |
    your-ai-profile-name-or-id
  # Endpoint Optional, default shown
  # endpoint: |
  #  https://service.api.aisecurity.paloaltonetworks.com

# mcpServers section requires at least one MCP Server.
mcpServers:
  # Example / demo MCP Servers
  homebrew:
    command: brew
    args:
      - mcp-server
    # Optional working directory, supports environment variables
    cwd: "${HOMEBREW_PREFIX}"
    # optional environment variables, inherited from the parent shell
    env:
      HOMEBREW_NO_ENV_HINTS: 1
  fetch:
    command: uvx
    args:
      - mcp-server-fetch

  # filesystem:
  #   command: npx
  #   args:
  #     - -y
  #     - '@modelcontextprotocol/server-filesystem'
  #     - /var/tmp/change/this/path
  #     # Command line arguments support environment variables
  #     - "${XDG_PICTURES_DIR}"

Environment Variables

In addition to CLI flags and the configuration file, pan-mcp-relay supports setting configuration through the following environment variables:

sh
# Required for Prisma AIRS API
PRISMA_AIRS_API_KEY=YOUR_API_KEY
# Required for Prisma AIRS API
PRISMA_AIRS_AI_PROFILE=YOUR_AI_PROFILE_NAME

# Optional, default is https://service.api.aisecurity.paloaltonetworks.com
PRISMA_AIRS_API_ENDPOINT=https://service.api.aisecurity.paloaltonetworks.com
# See https://pan.dev/prisma-airs/scan/api/#scan-api-endpoints for additional regional API endpoints

# Defaults shown for all other Environment Variables
MCP_RELAY_CONFIG_FILE=~/.config/pan-mcp-relay/mcp-relay.yaml
MCP_RELAY_TRANSPORT=stdio
# Host For SSE Transport Mode
MCP_RELAY_HOST=127.0.0.1
# Port for SSE Transport Mode
MCP_RELAY_TOOL_CACHE_TTL=86400
MCP_RELAY_MAX_SERVERS=32
MCP_RELAY_MAX_TOOLS=256
# Path to optional .env file
MCP_RELAY_DOTENV=
# Supports $PATH-style colon-separated list and environment variables. Directory entries will search for a file named `.env`
# MCP_RELAY_DOTENV=$HOME/.env:~/.config/pan-mcp-relay:$PWD

MCP_RELAY_LOG_LEVEL=INFO

MCP Client Configuration

Create a new config file mcp-relay.json to use with your MCP Client (IDE, Chat Client, or Agent).

json
{
  "mcpServers": {
    "pan-mcp-relay": {
      "command": "uvx",
      "args": [
        "pan-mcp-relay@latest"
      ]
    }
  }
}

For faster startup times, install/upgrade pan-mcp-relay using uv tool install --upgrade pan-mcp-relay, and use the command name directly:

json
{
  "mcpServers": {
    "pan-mcp-relay": {
      "command": "pan-mcp-relay"
    }
  }
}

[!CAUTION]

pan-mcp-relay should be the only MCP Server listed in your MCP Client configuration file.

Any other MCP Servers listed here will NOT be visible to the security capabilities of the MCP Relay.

Optionally, specify additional environment variables or CLI flags:

json
{
  "mcpServers": {
    "pan-mcp-relay": {
      "command": "uvx",
      "args": [
        "pan-mcp-relay",
        "--config-file",
        "~/.config/pan-mcp-relay/mcp-relay.yaml"
      ],
      "env": {
        "PRISMA_AIRS_AI_PROFILE": "your-ai-profile",
        "MCP_RELAY_LOG_LEVEL": "WARNING"
      }
    }
  }
}

Transport Options

The MCP Relay Server supports the standard MCP transport mechanisms:

  • stdio Transport: For local process communication (default)
  • Streamable Transport: For HTTP-based communication, supporting SSE (Server-Sent Events).
  • SSE Transport: For backwards compatibility with SSE-only MCP Clients.

Usage

pan-mcp-relay CLI Usage

terminaloutput
pan-mcp-relay --help
Usage: pan-mcp-relay [OPTIONS] COMMAND [ARGS]...

  Run the MCP Relay Server.

Options:
  -k, --api-key TEXT              Prisma AIRS API Key [PRISMA_AIRS_API_KEY=]
  -e, --api-endpoint TEXT         Prisma AIRS API Endpoint [PRISMA_AIRS_API_ENDPOINT=]
  -p, --ai-profile TEXT           Prisma AIRS AI Profile Name or ID [PRISMA_AIRS_AI_PROFILE=]
  -c, --config-file FILE          Path to configuration file (yaml, json) [MCP_RELAY_CONFIG_FILE=]
  -t, --transport [stdio|sse|http]
                                  Transport protocol to use [MCP_RELAY_TRANSPORT=]  [default: stdio]
  -h, --host TEXT                 Host for HTTP/SSE server [MCP_RELAY_HOST=]  [default: 127.0.0.1]
  -p, --port INTEGER              Port for HTTP/SSE server [MCP_RELAY_PORT=]  [default: 8000]
  -TTL, --tool-registry-cache-ttl INTEGER
                                  Tool registry cache TTL (in seconds) [MCP_RELAY_TOOL_CACHE_TTL=]  [default: 86400]
  -MS, --max-mcp-servers INTEGER  Maximum number of downstream MCP servers to allow [MCP_RELAY_MAX_SERVERS=]  [default: 32]
  -MT, --max-mcp-tools INTEGER    Maximum number of MCP tools to allow [MCP_RELAY_MAX_TOOLS=]  [default: 256]
  --env TEXT                      Use ./.env file, or specify colon separated path to .env file(s)or directories containing .env files. [MCP_RELAY_DOTENV=]
  --system-ca                     Use System CA instead of Mozilla CA Bundle
  --capath FILE                   Path to Custom Trusted CA bundle
  -d, --debug                     Extremely verbose logging output (DEBUG)
  -v, --verbose                   Verbose logging output (INFO, DEFAULT)
  -q, --quiet                     Minimal logging output (WARNING)
  --show-config, --dump-config    Show configuration and exit [MCP_RELAY_SHOW_CONFIG=]
  -V, --version                   Show the version and exit.
  --help                          Show this message and exit.

Commands:
  json-schema  Print Configuration File JSON Schema, optionally to a file.
  run          Run the MCP Relay Server.
  show-config  Print MCP Relay Configuration and exit.

Running the Relay Server

stdio transport (default)

sh
# Run with stdio transport with automatic configuration detection (default)
uvx pan-mcp-relay

# Specify a configuration file
uvx pan-mcp-relay --config-file ~/.config/pan-mcp-relay/mcp-relay.yaml

# Specify a path to a custom .env file
uvx pan-mcp-relay --env /var/run/secrets/.env

Streamable HTTP transport

sh
# Run with Streamable transport
pan-mcp-relay --transport=http

SSE transport

sh
# Run with SSE transport
pan-mcp-relay --transport=sse

Legal

Copyright © 2025, Palo Alto Networks

Licensed under the Polyform Internal Use License 1.0.0 (the "License"); you may not use this file except in compliance with the License.

You may obtain a copy of the License at:

https://polyformproject.org/licenses/internal-use/1.0.0

(or)

https://github.com/polyformproject/polyform-licenses/blob/76a278c4/PolyForm-Internal-Use-1.0.0.md

As far as the law allows, the software comes as is, without any warranty or condition, and the licensor will not be liable to you for any damages arising out of these terms or the use or nature of the software, under any kind of legal claim.

Installation

TypingMind
{
  "mcpServers": {
    "pan-mcp-relay": {
      "command": "uvx",
      "args": [
        "pan-mcp-relay"
      ]
    }
  }
}

Use Prisma AIRS MCP 安全中继 MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Prisma AIRS MCP 安全中继 is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Prisma AIRS MCP 安全中继 as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Prisma AIRS MCP 安全中继 MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "pan-mcp-relay": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Prisma AIRS MCP 安全中继 MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Prisma AIRS MCP 安全中继 MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Prisma AIRS MCP 安全中继 to help me with this task?
Prisma AIRS MCP 安全中继
Sure. I read it.
Here is what I found using Prisma AIRS MCP 安全中继.

Frequently asked questions

What is the Prisma AIRS MCP 安全中继 MCP server used for?

Prisma AIRS MCP 安全中继 is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Prisma AIRS MCP 安全中继 MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Prisma AIRS MCP 安全中继 with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Prisma AIRS MCP 安全中继 MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Prisma AIRS MCP 安全中继 connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Prisma AIRS MCP 安全中继 MCP to TypingMind?

Prisma AIRS MCP 安全中继 runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Prisma AIRS MCP 安全中继 MCP provide in TypingMind?

Prisma AIRS MCP 安全中继 exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Prisma AIRS MCP 安全中继 MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Prisma AIRS MCP 安全中继 requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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