MCP Server installation on Linux via Docker

Overview

This guide covers the installation of CAST Imaging MCP Server on Linux via Docker. It’s intended for:

• Direct installation on Linux, via Docker
• new installations (i.e. from scratch)
• in-place updates to a new release

The installation package com.castsoftware.imaging.mcpserver.docker  includes an installation script and configuration files. All Docker images are pulled direct from https://hub.docker.com  during the installation.

Requirements

MCP Server is a standalone component and can therefore be installed wherever convenient in your local environment, e.g. on a dedicated machine, or on a machine already used by other CAST Imaging components.

When using a dedicated machine, CAST recommends following the general hardware and software requirements but note that the component does not require:

• a Java JRE/JDK

Other requirements:

• MCP Server runs as a Docker container on TCP port 8282 although you can change this in the .env file (see below). You may therefore need to adjust firewall rules to allow incoming and outgoing connections to this port
• see software requirements for more information about supported Linux OS, Docker Engine and Docker Compose
• a minimum of 2GB free disk space
• CAST Imaging ≥ 3.4.1 installed and functioning (MCP Server interacts with the imaging-services component) in your network
• an MCP-aware client such as GitHub Copilot (Visual Studio Code)
• a CAST Imaging API key, see Generating an API key

What’s new?

See the release notes.

Installation process

Step 1 - Verify connection to CAST Imaging

Before proceeding, ensure you can access CAST Imaging (the imaging-services component) from the machine where you intend to install MCP Server by running the following (tailored to your own environment):

curl -H "x-api-key: <your-imaging-api-key>" http://<your_imaging_public_URL>:8090/rest/ready

The expected output is true.

Step 2 - Download the installation media

Download the installer using curl:

curl -# -O -J "https://extend.castsoftware.com/#/extension?id=com.castsoftware.imaging.mcpserver.docker/<version>?platform=linux_x64" -H "x-nuget-apikey: <api-key>" -H "accept: application/octet-stream"

Where:

• -#: enables a download progress bar.
• -O: (--remote-name) ensures the file is downloaded and saved to the current folder using the same name as the remote file.
• -J: (--remote-header-name) ensures the -O option uses the server-specified Content-Disposition filename instead of extracting a filename from the URL. If the server-provided filename contains a path, that is stripped off before the filename is used.
• <version>: use latest to download the most recent release, or specify the specific release, e.g., 1.0.1-funcrel.
• -H: (--header) defines the additional header to include in information sent.
• <api-key>: your CAST Extend API key (obtain this from https://extend.castsoftware.com/#/profile/settings )

Example for latest release:

curl -# -O -J "https://extend.castsoftware.com/#/extension?id=com.castsoftware.imaging.mcpserver.docker/latest?platform=linux_x64" -H "x-nuget-apikey: a9999a9a-c999-999d-999b" -H "accept: application/octet-stream"

Unzip the resulting ZIP file anywhere on your local disk. The following files/folders will be created:

com.castsoftware.imaging.mcpserver.docker.<version>/
├── config/
│   └── app.config
├── nginx/
│   └── nginx.conf
├── .env                        # Hidden file (use `ls -a` to view)
├── copilot-instructions.md
├── docker-compose.https.yml
├── docker-compose.yml
├── README.md
└── run.sh

Step 3 - Configure your installation

app.config

Locate the config/app.config file at the root of the unzipped installation media. Open the file with a text editor and update the installation variables to match your environment:

HOSTNAME_CONTROL_PANEL="imaging-services machine"      # Required: IP address/hostname/FQDN of the machine on which the "imaging-services" component is installed. You can use localhost if MCP Server is installed on the same machine as the "imaging-services" component.
PORT_CONTROL_PANEL=8098                               # Default port on which the CAST Imaging Control Panel service (part of the "imaging-services" component) is running - unless you have changed this during the CAST Imaging installation, leave it as is
IMAGING_PAGE_SIZE=1000                                # Sets the number of records the MCP server fetches per request (internal batching).
IMAGING_DISPLAY_PAGE_SIZE=20                          # Sets how many records are shown per page in the user-facing response
IMAGING_CODE=False                                    # Defines whether the application source code is accessible to the MCP Server or not: when it is set to False source code (from the Imaging analysis results) cannot be accessed by the MCP Server and therefore source code will not figure in any results returned by MCP server
HTTPS_ENABLED=false                                   # Enable HTTPS between MCP-aware client and MCP Server (requires appropriate certificates). Forces the use of the docker-compose.https.yml file instead of docker-compose.yml

.env

Locate the .env file at the root of the unzipped installation media. Open the file with a text editor and set the MCP server listening port (the default is set to 8282):

MCP_SERVER_PORT=8282    # Default port

Optional: establishing a HTTPS connection between the MCP-aware client and the MCP Server

If you need to establish a secure HTTPS connection between the MCP-aware client and MCP server, follow these steps:

1. Locate the config/app.config file at the root of the unzipped installation media. Open the file with a text editor and update the HTTPS_ENABLED variable to true:

HTTPS_ENABLED=true

2. Create a folder named certificates in the root of the unzipped installation media folder. Inside this folder, add your certificate and private key files with the following names:

• certificate.pem – the secure certificate
• private_key.pem – the corresponding private key

Step 4 - Run the installation

Run the following commands:

chmod +x run.sh    # makes the installation script executable
./run.sh

Verify the installation by checking Docker containers (you should see one Docker container hosting the MCP Server):

docker ps

Step 5 - Configure your MCP-Aware client (GitHub Copilot for Visual Studio Code)

Install GitHub Copilot extension

Install the GitHub Copilot extension (see https://marketplace.visualstudio.com/items?itemName=GitHub.copilot ) in Visual Studio Code, ensure you are signed in to GitHub and clone the repository you need to work with.

Create mcp.json file

Create an mcp.json configuration file and place it in the .vscode/ folder for your Visual Studio Code workspace. The mcp.json must use the following template:

{
  "inputs": [
    {
      "id": "imaging-key",
      "type": "promptString",
      "description": "CAST Imaging API Key"
    }
  ],
  "servers": {
    "imaging": {
      "type": "http",
      "url": "http://<your-mcp-server-host:port>/mcp/",
      "headers": {
        "x-api-key": "${input:imaging-key}"
      }
    }
  }
}

where:

• "type" is set to http or https depending on whether the MCP Server is set to run in secure HTTPS mode or not
• "url" is the IP address/hostname/FQDN and port number (8282 by default) of the machine hosting the MCP Server.

Manage copilot-instructions.md file

Locate the copilot-instructions.md file at the root of the unzipped installation media and copy it into a folder called .github located at the root of the repository you are working with. This file provides provide chat responses that are tailored to CAST Imaging: the additional information is not displayed in the chat, but is available to Copilot to allow it to generate higher quality responses.

Alternative manual registration flow

If Visual Studio Code does not auto‑pick the MCP server:

1. Open Copilot Chat → gear icon → Select tools that are available to chat
2. + Add More Tools… → + Add MCP Server… → choose HTTP
3. Enter http(s)://<your-mcp-server-host:port>/mcp/ and confirm
4. Visual Studio Code will then create .vscode/copilot/mcp.json → add the header block:

"my-mcp-server-xxxx": {
  "url": "http://<your-mcp-server-host:port>/mcp/",
  "headers": {
    "x-api-key": "${input:imaging-key}"
  }
}

Step 6 - Test your MCP-Aware client

1. Launch your MCP-aware client
2. Enter your CAST Imaging API key when prompted
3. Run a test query, for example:

List all applications
List 5 transactions for application <YourApp>
List available applications datagraphs
List applications insights

If successful (see below), you’re ready to use your MCP Client with your MCP Server.

Success indicators

✅ Connection successful if you receive:

• Valid application listings
• Architectural insights
• Suggested analysis queries

❌ Check configuration if you see:

• Connection errors
• Authentication failures
• Empty responses

Example queries

Basic application information

List all applications

Transaction analysis

List all applications transactions
Show 10 transactions for application <YourApp>

Data flow analysis

List available applications datagraphs
Show data graphs for application <YourApp>

Quality insights

List applications insights
Show quality issues for application <YourApp>

Architectural analysis

Analyze the architecture of <YourApp>
Show dependencies for <YourApp>

Available Toolsets

Tools

Troubleshooting

1. Check the MCP Server container is running:

docker ps | grep imaging-mcp

2. Check MCP Server logs:

docker logs <mcp-container-id>

3. Test connectivity to CAST Imaging API:

curl -H "x-api-key: <your-imaging-api-key>" http://<your_imaging_public_URL>:8090/rest/ready

4. Validate configuration files:

• Check config/app.config
• Check .env file for correct port configuration
• Ensure "url" parameter in the client mcp.json points to correct URL

5. Regenerate API key in CAST Imaging profile if necessary.

Uninstall process

To remove only MCP Server related items:

• run the following Docker commands
• delete the installer ZIP file
• delete the unzipped installation files/folder

# Stop imaging-services containers
cd /<unzipped-install-files>
docker compose down

# Remove images
docker images | grep $servicename | awk '{print $3}' | xargs -I {} docker rmi -f {}
docker image prune