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About MCP integration🔗

HDevelopEVO integrates the Model Context Protocol (MCP), enabling you to configure and utilize external services in your AI workflows.

Preview restriction

While this integration does not yet include MCP servers in any standard prompts, it already allows you to explore the MCP ecosystem and discover interesting new use cases.

To learn more about MCP, see the official announcement from Anthropic. For a list of available MCP servers, visit the MCP Servers Repository.

Configuring MCP servers🔗

To configure MCP servers, open the Preferences and add entries to the MCP Servers Configuration section. Each server requires a unique identifier, for example, brave-search or filesystem, and configuration details such as the command, arguments, optional environment variables and autostart.

autostart, true by default, will automatically start the respective MCP server whenever you restart HDevelopEVO. In your current session, however, you’ll still need to manually start it using the MCP Start MCP Server command.

MCP example configuration 
{
  "brave-search": {
    "command": "npx",
    "args": [
      "-y",
      "@modelcontextprotocol/server-brave-search"
    ],
    "env": {
      "BRAVE_API_KEY": "YOUR_API_KEY"
    },
    "autostart": false
  },
  "filesystem": {
    "command": "npx",
    "args": [
      "-y",
      "@modelcontextprotocol/server-filesystem",
      "/Users/YOUR_USERNAME/Desktop"
    ],
    "env": {
      "CUSTOM_ENV_VAR": "custom-value"
    }
  },
  "git": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/repo",
        "run",
        "mcp-server-git"
      ]
    },
  "git2": {
      "command": "uvx",
      "args": [
        "mcp-server-git",
        "--repository",
        "/path/to/otherrepo"
      ]
  }
}

Note

uvx comes preinstalled with uv and does not need to be installed manually. Running pip install uvx installs a deprecated tool unrelated to uv.

The configuration options include:

  • command: Executable used to start the server (for example, npx)
  • args: Array of arguments passed to the command
  • env: Optional set of environment variables for the server

Windows users

On Windows, you need to start a command interpreter (for example, cmd.exe) as the server command in order for path lookups to work as expected. The effective command line is then passed as an argument.

For example:

"filesystem": {
    "command": "cmd",
    "args": ["/C", "npx -y @modelcontextprotocol/server-filesystem /Users/YOUR_USERNAME/Desktop"],
    "env": {
        "CUSTOM_ENV_VAR": "custom-value"
    }
  }

Starting and stopping MCP servers🔗

HDevelopEVO provides commands to manage MCP servers:

Start MCP Server
Use the command MCP: Start MCP Server to start a server. The system displays a list of available servers to select from.
Stop MCP Server
Use the command MCP: Stop MCP Server to stop a running server.

When a server starts, a notification is displayed confirming the operation, and the functions made available. You can also set a MCP server to autostart in the settings, true by default.

Note

In a browser deployment MCP servers are scoped per connection, that is, if you manually start them, you need to start them once per browser tab.

Using MCP server functions🔗

Once a server is running, its functions can be invoked in prompts using the following syntax:

~{mcp_<server-name>_<function-name>}
  • mcp: Prefix for all MCP commands
  • <server-name>: Unique identifier of the server (for example, brave-search)
  • <function-name>: Specific function exposed by the server (for example, brave_web_search)

Example

To use the brave_web_search function of the brave-search server, you can write: 

~{mcp_brave-search_brave_web_search}

This allows you to seamlessly integrate external services into your AI workflows.