Enables installing and configuring MCP servers from GitHub repositories, with support for authentication via personal access tokens
Provides configuration support for the MCP installer on macOS systems
Provides installation of MCP servers published as npm packages
Supports installation of MCP servers published as Python packages on PyPI
Mentioned as a potential MCP server that can be installed via this installer
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 Installer install the MCP server named mcp-server-fetch for me"
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.
This server is a server that installs other MCP servers for you. Install it, and you can ask Claude to install MCP servers hosted in npm or PyPi for you. Requires npx and uv to be installed for node and Python servers respectively.
Put this into your claude_desktop_config.json (either at ~/Library/Application Support/Claude on macOS or C:\Users\NAME\AppData\Roaming\Claude on Windows):
"mcpServers": {
"mcp-installer": {
"command": "npx",
"args": [
"@anaisbetts/mcp-installer"
]
}
}Hey Claude, install the MCP server named mcp-server-fetch
Hey Claude, install the @modelcontextprotocol/server-filesystem package as an MCP server. Use ['/Users/anibetts/Desktop'] for the arguments
Hi Claude, please install the MCP server at /Users/anibetts/code/mcp-youtube, I'm too lazy to do it myself.
Install the server @modelcontextprotocol/server-github. Set the environment variable GITHUB_PERSONAL_ACCESS_TOKEN to '1234567890'
Install an MCP server whose code is cloned locally on your computer
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | The path to the MCP server code cloned on your computer | |
| args | No | The arguments to pass along | |
| env | No | The environment variables to set, delimited by = |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is 'Install', implying a write operation, but doesn't cover permissions needed, side effects (e.g., system changes), error handling, or output format. This leaves significant gaps for a tool that likely modifies the local environment.
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 that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized, making it easy to parse quickly.
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 complexity of an installation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., what 'Install' entails operationally), prerequisites, or expected outcomes, leaving the agent with incomplete context for safe and effective use.
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?
Schema description coverage is 100%, so the schema already documents all three parameters (path, args, env) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints, resulting in the baseline score for high schema coverage.
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 clearly states the action ('Install') and the resource ('an MCP server whose code is cloned locally on your computer'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'install_repo_mcp_server' beyond the 'cloned locally' detail, which is implied but not contrasted.
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 versus alternatives like 'install_repo_mcp_server' or 'add_to_cursor_config'. It mentions the resource is 'cloned locally', which hints at a prerequisite, but lacks explicit when/when-not instructions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Install an MCP server via npx or uvx
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | The package name of the MCP server | |
| args | No | The arguments to pass along | |
| env | No | The environment variables to set, delimited by = |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but lacks behavioral details. It states the installation action but doesn't disclose critical traits like required permissions, side effects (e.g., system changes), error handling, or output format. This leaves significant gaps for an agent to understand the tool's behavior.
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 zero waste. It's front-loaded with the core action and methods, making it easy to parse quickly 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 complexity of installing software (a mutation operation with potential side effects), no annotations, and no output schema, the description is incomplete. It lacks details on prerequisites, success/failure outcomes, and behavioral context, making it insufficient for safe and effective tool invocation.
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?
Schema description coverage is 100%, so the schema already documents all parameters (name, args, env). The description adds no additional meaning beyond what the schema provides, such as examples or usage context for parameters. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 clearly states the action ('Install') and resource ('MCP server'), specifying the installation methods ('via npx or uvx'). However, it doesn't differentiate from sibling tools like 'install_local_mcp_server', which likely handles local installations versus this tool's package-based approach.
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?
No explicit guidance on when to use this tool versus alternatives is provided. The description mentions installation methods but doesn't clarify scenarios where 'install_repo_mcp_server' is preferred over 'install_local_mcp_server' or other siblings, leaving usage context ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
install_local_mcp_serverinstall_repo_mcp_serverScored across 2 tools
The two tools have clearly distinct purposes: one installs from local code, the other installs via package managers (npx/uvx). There is no overlap or ambiguity between them.
Both tools follow a consistent verb_noun pattern with 'install' as the verb and descriptive suffixes ('local_mcp_server', 'repo_mcp_server'). The naming is perfectly uniform and predictable.
With only 2 tools, the server feels thin for an 'Installer' domain. While it covers two installation methods, it lacks tools for managing installations (e.g., list, update, remove), making the surface incomplete for typical installer workflows.
The toolset is severely incomplete for an installer. It provides installation methods but lacks essential operations like listing installed servers, updating them, uninstalling, or checking status. This will cause agent failures for common management tasks.
Hosted MCP server connecting claude.ai, ChatGPT and other AI apps to your own computer
Augments MCP Server - A comprehensive framework documentation provider for Claude Code
The Remote MCP server acts as a standardized bridge between LLM applications (like Claude, ChatGPT, and Cursor) and external services, enabling AI agents to access external tools and resources. Its primary capability is providing a centralized search tool to discover other MCP servers and their respective tools. Unlike local implementations, it runs remotely with OAuth authentication and permission controls for security.
Search and install 4,000+ security-scanned MCP servers from inside any MCP-aware AI client.
