Allows models to interact with an active iTerm terminal session, including writing commands, reading terminal output, and sending control characters. Enables the model to execute commands, work with REPLs, and view specific portions of terminal output.
Provides integration with macOS through the iTerm2 terminal, allowing interaction with the macOS system via terminal commands.
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., "@iTerm MCP list files in the current directory"
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.
A Model Context Protocol server that provides access to your iTerm session.
Efficient Token Use: iterm-mcp gives the model the ability to inspect only the output that the model is interested in. The model typically only wants to see the last few lines of output even for long running commands.
Natural Integration: You share iTerm with the model. You can ask questions about what's on the screen, or delegate a task to the model and watch as it performs each step.
Full Terminal Control and REPL support: The model can start and interact with REPL's as well as send control characters like ctrl-c, ctrl-z, etc.
Easy on the Dependencies: iterm-mcp is built with minimal dependencies and is runnable via npx. It's designed to be easy to add to Claude Desktop and other MCP clients. It should just work.
The user is responsible for using the tool safely.
No built-in restrictions: iterm-mcp makes no attempt to evaluate the safety of commands that are executed.
Models can behave in unexpected ways. The user is expected to monitor activity and abort when appropriate.
For multi-step tasks, you may need to interrupt the model if it goes off track. Start with smaller, focused tasks until you're familiar with how the model behaves.
write_to_terminal - Writes to the active iTerm terminal, often used to run a command. Returns the number of lines of output produced by the command.
read_terminal_output - Reads the requested number of lines from the active iTerm terminal.
send_control_character - Sends a control character to the active iTerm terminal.
iTerm2 must be running
Node version 18 or greater
Related MCP server: MCP Terminal
To use with Claude Desktop, add the server config:
On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"iterm-mcp": {
"command": "npx",
"args": [
"-y",
"iterm-mcp"
]
}
}
}To install iTerm for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install iterm-mcp --client claudeInstall dependencies:
yarn installBuild the server:
yarn run buildFor development with auto-rebuild:
yarn run watchSince MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
yarn run inspector
yarn debug <command>The Inspector will provide a URL to access debugging tools in your browser.
Reads the output from the active iTerm terminal
| Name | Required | Description | Default |
|---|---|---|---|
| linesOfOutput | Yes | The number of lines of output to read. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It doesn't disclose whether this requires specific permissions, how it handles errors (e.g., if no terminal is active), what format the output returns, or any rate limits. The description only states what it does, not how it behaves.
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's front-loaded and appropriately sized for a simple tool, with zero wasted information.
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 no annotations and no output schema, the description is incomplete for a tool that interacts with a terminal. It lacks details on behavioral traits (e.g., error handling, output format), usage context, and doesn't compensate for the absence of structured data, making it insufficient for reliable agent 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 input schema has 100% description coverage, fully documenting the single parameter 'linesOfOutput'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without extra value.
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 ('Reads') and target resource ('output from the active iTerm terminal'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'write_to_terminal' or 'send_control_character', which would require mentioning it's for reading rather than writing or control operations.
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 prerequisites (e.g., having an active terminal), exclusions, or comparisons to sibling tools, leaving the agent to infer usage context solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Sends a control character to the active iTerm terminal (e.g., Control-C)
| Name | Required | Description | Default |
|---|---|---|---|
| letter | Yes | The letter corresponding to the control character (e.g., 'C' for Control-C) |
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 ('Sends') but doesn't clarify effects (e.g., whether it interrupts running commands, requires specific terminal state, or has side effects like closing sessions). The example 'Control-C' hints at interruption, but explicit behavioral traits like permissions or terminal requirements are missing.
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 core action with a clarifying example. There is no wasted text, and it directly addresses the tool's purpose without unnecessary elaboration, making it highly concise and well-structured.
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 a tool that interacts with a terminal (potentially affecting running processes), the description is incomplete. With no annotations and no output schema, it lacks details on behavioral impact, error conditions, or return values. The example helps but doesn't cover broader usage or constraints, leaving gaps 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?
The schema description coverage is 100%, with the parameter 'letter' fully documented in the schema. The description adds minimal value by providing an example ('C' for Control-C), which reinforces the schema but doesn't elaborate on semantics like valid letters, case sensitivity, or special characters beyond what the schema implies.
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 ('Sends') and target ('active iTerm terminal'), with a specific example ('Control-C') that clarifies the type of operation. It distinguishes from sibling tools like 'read_terminal_output' and 'write_to_terminal' by focusing on control characters rather than reading or writing text. However, it doesn't explicitly mention what resource is being affected beyond the terminal.
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 is provided on when to use this tool versus alternatives. The description implies usage for sending control characters, but doesn't specify scenarios (e.g., interrupting processes, sending signals) or contrast with sibling tools like 'write_to_terminal' for regular text input. This leaves the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Writes text to the active iTerm terminal - often used to run a command in the terminal
| Name | Required | Description | Default |
|---|---|---|---|
| command | Yes | The command to run or text to write to the terminal |
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 tool writes to the 'active' terminal and can run commands, but doesn't address important behavioral aspects like whether this requires specific permissions, whether it waits for command completion, what happens if no terminal is active, or potential side effects of command execution. The description is insufficient for a mutation 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 extremely concise (one sentence) with zero wasted words. It's front-loaded with the core functionality ('writes text to the active iTerm terminal') followed by a usage hint. Every element earns its place in this minimal description.
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?
For a mutation tool with no annotations, no output schema, and a single parameter, the description is incomplete. It doesn't address important contextual aspects like error conditions, what constitutes 'active' terminal, whether the tool blocks until command completion, or what happens after command execution. The description provides basic functionality but lacks sufficient operational context.
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 fully documents the single 'command' parameter. The description adds marginal value by suggesting the parameter can contain either 'text to write' or 'command to run', but doesn't provide additional syntax, format, or constraint details beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.
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 specific verbs ('writes text', 'run a command') and identifies the target resource ('active iTerm terminal'). It distinguishes from sibling 'read_terminal_output' by focusing on output rather than input, though it doesn't explicitly contrast with 'send_control_character'.
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 implied usage context ('often used to run a command in the terminal'), suggesting this is for executing commands rather than just writing text. However, it doesn't explicitly state when to use this tool versus 'send_control_character' or provide any exclusion criteria or prerequisites for usage.
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.
read_terminal_outputsend_control_characterwrite_to_terminalEach tool has a clearly distinct purpose: reading output, sending control characters, and writing text/commands. There is no overlap in functionality, making it easy for an agent to select the right tool for each operation.
All tool names follow a consistent verb_noun pattern (read_terminal_output, send_control_character, write_to_terminal). The naming is uniform and predictable, using snake_case throughout with clear action-object pairs.
With only 3 tools, the set feels minimal but covers core terminal interactions. For a terminal control server, this is borderline thin, as additional operations like listing sessions or managing tabs might be expected, but it's not severely lacking.
The tools cover essential terminal operations: reading, writing, and sending control signals. Minor gaps exist, such as no tools for managing multiple terminals or sessions, but the core workflow for interacting with an active terminal is well-supported without dead ends.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
A Model Context Protocol server for Wix AI tools
Talk to your public-facing AI from any MCP client — Claude, ChatGPT, Cursor, Cline, Windsurf.
Real-time chat for AI agents. Claude Code, Cursor, Cline and Codex join channels over MCP.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/lite/iterm-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server
