Provides read-only access to macOS system information through native terminal utilities, including disk management, battery status, network configuration, and system profiler data.
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., "@macOS Tools MCP Server show me my battery status"
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.
FastMCP server that makes a handful of read-only macOS terminal utilities available to MCP clients.
macOS 12 or newer (tools require native system binaries)
uv for dependency and virtual environment management
Python 3.11 (automatically managed by uv via .python-version)
Related MCP server: mcp-system-info
Install dependencies and create the virtual environment:
uv syncLaunch the MCP server:
uv run macos-tools-mcpThe FastMCP server starts with default settings and exposes the registered tools.
diskutil_list – lists disks and partitions by invoking diskutil list.
battery_status – reports battery information from pmset -g batt.
network_services – enumerates configured network services via networksetup.
network_service_details – retrieves IP/subnet/router info for a given network service (for example Wi-Fi).
system_profile – returns structured JSON from system_profiler; accepted aliases are software, hardware, network, and power.
Execute uv run python -m macos_tools_mcp.server to run the server module directly.
The helper module macos_tools_mcp.tools centralizes command invocation and validation logic if you need to add more tools.
Show current battery information reported by pmset -g batt.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 what command will be executed ('pmset -g batt') but doesn't describe what happens when invoked - whether it requires permissions, how long it takes, what format the output will be in, or any error conditions. For a tool with zero annotation coverage, this is a significant gap in behavioral transparency.
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 extremely concise - a single sentence that directly states what the tool does and how it works. Every word earns its place: 'Show current battery information' defines the purpose, and 'reported by `pmset -g batt`' provides implementation context. There's zero waste or redundancy.
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 that the tool has no parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete for its complexity level. However, for a system tool that executes a shell command, the description could benefit from mentioning typical output format or common use cases. The existence of an output schema means the description doesn't need to explain return values, but additional context about the tool's behavior would be helpful.
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 already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist. This earns a baseline 4 for parameter semantics as the description doesn't need to compensate for any parameter documentation gaps.
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 tool's purpose: 'Show current battery information' with the specific source 'reported by `pmset -g batt`'. This provides a specific verb ('show') and resource ('battery information') with implementation details. However, it doesn't explicitly differentiate from sibling tools like 'system_profile' which might also provide system information.
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. It doesn't mention when this tool is appropriate versus using 'system_profile' or other system monitoring tools, nor does it provide any context about prerequisites, timing considerations, or limitations. The agent must infer usage from the tool name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all disks and partitions using diskutil list.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 but doesn't describe what the output looks like (though an output schema exists), whether it requires admin privileges, if it's read-only or has side effects, or any rate limits. This is a significant gap for a tool with zero annotation coverage.
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 purpose and includes the specific command, making it appropriately sized and well-structured for its simplicity.
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 tool's low complexity (0 parameters, output schema provided), the description is somewhat complete but has gaps. It states what the tool does but lacks behavioral context and usage guidelines. The output schema helps, but the description doesn't leverage this to explain return values or other aspects, making it minimally adequate.
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 lack of parameters. The description doesn't need to add parameter details, and it correctly implies no inputs are required by not mentioning any. Baseline for 0 parameters is 4, as it's complete in this regard.
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 ('List all disks and partitions') and the specific command used ('using `diskutil list`'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'system_profile' which might also provide system information, so it doesn't reach the highest 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 versus alternatives like 'system_profile' or other system information tools. There's no mention of context, prerequisites, or exclusions, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve interface details (IP, subnet, router) for a network service.
| Name | Required | Description | Default |
|---|---|---|---|
| service_name | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'Retrieve', implying a read-only operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, error handling, or what happens if the service doesn't exist. This is a significant gap for a tool with no annotation coverage.
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 front-loads the purpose with no wasted words. It directly states what the tool does without unnecessary elaboration, 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 tool has an output schema (which covers return values), no annotations, and low complexity, the description is minimally adequate. However, it lacks context on usage, behavioral transparency, and parameter details, leaving gaps that could hinder correct tool selection and 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?
The schema has 0% description coverage, so the description must compensate. It implies 'service_name' is used to identify the network service, but doesn't add meaning beyond that (e.g., format, examples, or valid values). With one parameter, the baseline is 4, but the description only partially compensates for the lack of schema details.
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 ('Retrieve') and the resource ('interface details for a network service'), specifying what information is retrieved (IP, subnet, router). It distinguishes from sibling tools like 'network_services' by focusing on details rather than listing services, though it doesn't explicitly contrast them.
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 guidance is provided on when to use this tool versus alternatives. The description implies it's for retrieving details of a specific network service, but it doesn't mention prerequisites, when not to use it, or how it relates to siblings like 'network_services' (which might list services).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List configured network services as reported by networksetup.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 mentions the data source (`networksetup`), which adds useful context about how the information is gathered, but doesn't describe output format, potential errors, or system dependencies. The description doesn't contradict annotations (since none exist), but it's minimal for a tool with no annotation coverage.
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, well-structured sentence that front-loads the key action ('List configured network services') and adds relevant context ('as reported by `networksetup`'). There is zero waste, and every word earns its place, making it highly concise and effective.
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 tool's simplicity (0 parameters, no annotations, but has an output schema), the description is reasonably complete. It clearly states what the tool does and the data source, which is sufficient for a listing tool. The output schema will handle return values, so the description doesn't need to explain them. However, it could benefit from more behavioral context or usage guidance.
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, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline score of 4 is appropriate—it efficiently states the tool's purpose without unnecessary parameter details.
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 tool's purpose with a specific verb ('List') and resource ('configured network services'), and mentions the source (`networksetup`). However, it doesn't explicitly differentiate from sibling tools like 'network_service_details', which might provide more detailed information about individual services.
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 'network_service_details' or other network-related tools. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return structured data from system_profiler for the requested data type.
| Name | Required | Description | Default |
|---|---|---|---|
| data_type | No | software |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
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 tool returns structured data but doesn't explain how it behaves—such as whether it's read-only, requires permissions, has rate limits, or what the output format entails. This leaves significant gaps in understanding the tool's operation.
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, clearly front-loading the tool's purpose. It's appropriately sized for a simple tool, 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 tool's low complexity (1 parameter, no nested objects) and the presence of an output schema, the description is somewhat complete but lacks critical context. It doesn't explain parameter semantics or behavioral traits, which are needed for effective use despite the output schema covering return values.
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 description mentions 'requested data type' but doesn't add meaning beyond the input schema, which has 0% coverage and only lists 'data_type' with a default. No details on valid data types, examples, or constraints are provided, failing to compensate for the low 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 ('Return structured data') and resource ('from `system_profiler`'), specifying the tool's function to retrieve system profiling information. However, it doesn't differentiate from sibling tools like 'battery_status' or 'diskutil_list' that also return system data, missing explicit distinction.
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 guidance is provided on when to use this tool versus alternatives. The description mentions 'requested data type' but doesn't specify what data types are available, when to choose this over sibling tools, or any prerequisites, leaving usage context unclear.
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. Dates show when Glama detected each change.
battery_statusdiskutil_listnetwork_service_detailsnetwork_servicessystem_profileEach tool has a clearly distinct purpose targeting different macOS system components: battery, disks, network services (listing vs. details), and system profile. There is no overlap in functionality, making tool selection straightforward for an agent.
The naming follows a consistent snake_case pattern with descriptive names (e.g., battery_status, diskutil_list). However, there is a minor deviation with 'network_service_details' and 'network_services' using slightly different naming styles (details vs. services) compared to the others, though still readable.
With 5 tools, the count is well-scoped for a macOS system utilities server. Each tool serves a specific, non-trivial purpose (battery, disks, network, system info), and there are no redundant or missing tools that would make the set feel too thin or bloated.
The toolset covers key macOS system areas (battery, storage, network, hardware/software info), but there are notable gaps in common system operations like process management, file operations, or user management. While the provided tools are useful, the surface is incomplete for broader system administration tasks.
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