mcp-get-installed-apps
The Get Installed Apps MCP Server allows AI assistants to retrieve a list of installed applications on your computer.
Discover Installed Apps: Returns a comprehensive list of installed applications on macOS and Windows.
MCP Integration: Seamlessly integrates with MCP-compatible AI clients like Claude, Raycast, and Cursor.
No Input Required: The
get-installed-appstool requires no parameters, making it easy to use.JSON Output: Provides structured data of installed apps or error information if the request fails.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-get-installed-appslist all my installed applications"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Get Installed Apps MCP Server
A Model Context Protocol (MCP) server that provides information about installed applications on your computer, support MacOS and Windows.
Project Introduction
Get Installed Apps MCP Server is a simple MCP implementation that allows AI assistants to discover which applications are installed on your computer. This server implements the Model Context Protocol (MCP) specification, enabling seamless integration with compatible AI clients.
Related MCP server: XcodeBuildMCP
Features
Returns a comprehensive list of installed applications on your computer
Simple integration with any MCP-compatible AI client
Lightweight implementation with minimal dependencies
Project Structure
mcp-get-installed-apps
├── src
│ ├── index.ts # Application entry point
├── tsconfig.json # TypeScript configuration file
├── package.json # npm configuration file
└── README.md # Project documentationInstallation
git clone https://github.com/Xutaotaotao/mcp-get-installed-apps.git
cd git-mcp-server
npm install
npm run buildMCP Configuration
After installation, you can configure Get Installed Apps MCP in your MCP JSON configuration:
{
"mcpServers": {
"get-installed-apps": {
"command": "node",
"args": [
"mcp-get-installed-apps/build/index.js"
]
}
}
}Configure the MCP JSON in the AI Client
Claude Client: https://modelcontextprotocol.io/quickstart/user
Raycast: requires installing the MCP plugin
Cursor: https://docs.cursor.com/context/model-context-protocol#configuring-mcp-servers
MCP Tool Description
Get Installed Apps MCP Server provides the following tool, which can be called through the MCP protocol:
Get Installed Apps (get-installed-apps)
Returns a list of all installed applications on your computer.
Parameters:
None
Returns:
Success: Text content containing JSON data of all installed applications
Failure: Text content containing error information
Available Tools
1 toolget-installed-appsB
Get my computer's installed apps
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Get' which implies a read operation, but fails to describe critical traits like whether this requires permissions, what format the output is in, if it's paginated, or any rate limits. For a tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is front-loaded with the core purpose, making it easy for an AI agent to quickly understand the tool's function without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not explain what the return values are (e.g., list format, data structure) or address behavioral aspects like permissions or errors. For a tool that retrieves system data, this leaves significant gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description does not need to add parameter information, and it appropriately avoids redundancy. A baseline of 4 is applied since no parameters exist, and the description does not introduce confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get my computer's installed apps' clearly states the action (get) and resource (installed apps) with a specific scope (my computer). It's not tautological with the tool name 'get-installed-apps' and provides a meaningful purpose. However, without sibling tools, the differentiation aspect is not applicable, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool, such as prerequisites, alternatives, or exclusions. It simply states what the tool does without context for usage, which is a significant gap in helping an AI agent make informed decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as retrieving installed apps from the computer, making it distinct by default.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'get-installed-apps' follows a clear verb-noun pattern, and there are no other tools to compare it against for inconsistency.
A single tool is too few for most server purposes, as it limits functionality and suggests a thin or incomplete surface. While it might be appropriate for a very narrow scope, it generally feels insufficient for typical agent workflows.
The server's domain appears to be managing installed apps, but with only a 'get' operation, there are significant gaps. Missing operations like install, uninstall, update, or search apps make the surface incomplete and likely to cause agent failures for broader tasks.
Maintenance
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