Desktop Commander Overview

ClineOfficialPublished by Cline

Skill
Tool integration
Automation and integrations
Apache-2.0
Low risk

From the author

Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.

— the description by Cline

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Desktop Commander MCP provides an agent with direct access to a user's local machine, enabling it to manage persistent shell sessions, long-running processes, and complex file operations. This skill documentation outlines how to leverage its capabilities for tasks ranging from remote SSH diagnostics and large-scale file searching to editing structured documents like Excel, DOCX, and PDF files. It emphasizes best practices such as using absolute paths, respecting directory scopes, and utilizing pagination to maintain context efficiency.

What it does

Maintains persistent shell and REPL sessions across multiple turns.
Manages long-running background processes like dev servers or test suites.
Performs surgical edits on text and structured files including Excel, DOCX, and PDF.
Executes large-scale content and filename searches using ripgrep.
Provides remote system access and diagnostics via persistent SSH sessions.
Offers process management tools to inspect, tail, and terminate system tasks.

When to use it

When you need to perform operations outside the IDE workspace.
When you need to maintain state in a shell or REPL across multiple agent turns.
When working with large data files like CSVs or complex structured documents.
When you need to monitor or interact with long-running background processes.
When performing refactoring or search tasks across an entire project directory.

Advantages

Enables stateful interaction with local terminals and remote servers.
Supports direct manipulation of binary and structured document formats.
Reduces context window bloat through efficient pagination and streaming.
Provides built-in safety mechanisms for file edits to prevent data corruption.
Allows for seamless integration of local data analysis workflows.

Usage examples

“Analyze the 200MB sales_data.csv file in my Downloads folder.”: The agent starts a persistent Python REPL, loads the CSV into a pandas DataFrame once, and performs requested analysis (e.g., df.describe()) without reloading the file.
“Update the Q3 revenue figures in the report.xlsx file.”: The agent reads the specific cell range as a JSON array, modifies the values, and writes the changes back to the original file while preserving its format.
“Debug the production server logs.”: The agent initiates an SSH session, tails the log file, and keeps the session open across multiple turns to run diagnostic commands based on log output.
“Refactor the function name 'old_func' to 'new_func' across the entire repository.”: The agent performs a scoped search, pages through results, and uses edit_block to perform precise replacements, verifying the completion by re-running the search.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/cline/desktop-commander-overview/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip desktop-commander-overview.zip -d .agents/skills

Documentation by Cline

Desktop Commander MCP

Desktop Commander gives the agent reach across the user's actual computer — files, folders, terminals, processes, structured documents, and remote machines reachable over SSH. The tools' detailed schemas (parameters, return shapes, format-specific behavior) live in the MCP itself; this skill explains what they enable and how they compose into common workflows.

What this MCP gives the agent

Persistent shell sessions. Desktop Commander keeps a started process or session alive across tool calls. Inside a single long-lived shell, REPL, or SSH session, state carries forward — environment variables, working directory, activated virtualenvs, open connections, REPL variables — so the agent can cd, activate a venv, then send commands or code into that same session many turns later without re-setup. (Note: separate start_process calls open separate sessions and do not share shell state with each other; persistence is inside one session, not across them.)

Long-running processes. Start a dev server, watcher, build, training run, or test suite in the background and keep working. The MCP returns a process handle the agent can tail, interact with, or terminate across many turns. Long-running commands don't need to block the workflow waiting for a foreground command to exit.

Filesystem reach beyond the IDE workspace. Read, write, move, list, and inspect files anywhere the user has granted scope — Downloads, Documents, project folders outside the IDE, or any other granted folders. Useful for organize-and-clean tasks, batch document work, and any "look at the file my coworker just sent me" request that doesn't fit inside the IDE sandbox.

Surgical edits to existing files. The edit_block tool does exact-string find-and-replace with built-in safety: ambiguous matches fail loudly instead of silently overwriting the wrong thing, and an expected_replacements count prevents partial-match disasters. Lower data-loss risk than rewriting whole files based on the slice you happened to read — though a wrong old_string or wrong expected_replacements can still corrupt content, so review the changed content before considering the edit done.

Binary and structured files handled directly by the MCP. Excel, DOCX, and PDF are first-class — read and modified through format-specific mechanisms rather than text-only approximations: Excel via cell-range JSON, DOCX via raw-XML edits, PDF via page-level operations on a new output file. The result is the real file in its original format, not a regenerated approximation. Images and PDFs return as viewable content for the agent.

Search at scale. Streaming, ripgrep-backed search across whole projects or folder trees. The agent picks between filename search and in-file content search, pages through results progressively without flooding context, and runs multiple concurrent searches when the query is ambiguous.

Remote machines via SSH. A long-lived SSH session inside a persistent shell turns the agent into a real ops tool: connect once, then tail logs, run diagnostics, deploy, or debug across many turns without reconnecting each step.

Process management. List, inspect, tail, and kill accessible processes (subject to OS permissions). Useful for cleaning up stale dev servers from previous sessions and for diagnosing CPU / memory issues.

Example workflows

Each example names the actual tool sequence. Calls below are written in pseudocode shorthand (tool_name("arg", flag=value)); the real tools take object-shaped arguments. Tool descriptions and full parameter sets live in the MCP itself.

"Debug this production issue"

Before running production-impacting SSH commands, explain the intended action and get user confirmation when the risk is non-trivial.

start_process("ssh [email protected]", timeout_ms=...) opens a long-lived SSH session and returns a PID. interact_with_process(pid, "tail -f /var/log/app.log\n") starts streaming logs. Subsequent turns: read_process_output(pid, offset=-50) to see the last 50 lines as they arrive, interact_with_process(pid, "...") to run diagnostic commands in the same session. force_terminate(pid) to close the session when done — for sessions opened by start_process, force_terminate is the correct cleanup tool; kill_process is for arbitrary OS PIDs found via list_processes.

"Deploy this to staging"

Before deploys, restarts, migrations, or other environment-changing commands, summarize the action and confirm with the user unless they already explicitly asked for that exact operation.

start_process for the deploy command (could be a script, an SSH-piped command, or kubectl/gh etc.). read_process_output to track output and surface errors. If the deploy needs an interactive confirmation, interact_with_process(pid, "yes\n"). The session stays alive while the agent watches for completion or rollback.

"Run the dev server and iterate on the API"

start_process("npm run dev", timeout_ms=...) keeps the server up. The agent then loops: edit_block on the route file, read_process_output(pid, offset=-30) to see the server's reload, start_process("curl -s http://localhost:3000/api/...") for a one-shot test, repeat. The dev server never has to restart between code changes.

"Refactor across this monorepo"

start_search(pattern="oldFunctionName", path=repo_root, searchType="content") scopes every call site. get_more_search_results(sessionId) pages through. read_multiple_files(paths=[...]) confirms ambiguous hits in context. edit_block(file_path, old_string, new_string) per site, with expected_replacements set when the same substring legitimately appears multiple times in one file. Verify by re-running start_search on the old name and paging the results with get_more_search_results(sessionId) until the run completes — only then can you confirm zero remaining hits.

"Update the Q3 numbers in this spreadsheet and tweak the summary in the report"

read_file(path="/.../q3.xlsx", sheet="Revenue", range="A1:F50") returns the existing numbers as a JSON 2D array. edit_block(file_path="/.../q3.xlsx", range="Revenue!C12:C24", content=[[12345], ...]) updates the cells in place. For the report, DOCX editing is a two-read flow: first read_file(path="/.../report.docx") (offset 0) returns the document's outline (headings + paragraph text) so you can locate the summary section. Then read_file(path="/.../report.docx", offset=N, length=...) with N > 0 returns the raw underlying XML around that section — a non-zero offset is what flips the read into XML mode. Copy an XML fragment from that output as old_string and call edit_block(file_path, old_string, new_string) with the rewritten XML. The user gets back real .xlsx and .docx files, not regenerated approximations.

"Generate the Q3 report as a PDF"

Compose markdown content (header, table, charts via embedded HTML), then call write_pdf to render it to a new PDF file. The MCP's write_pdf tool description specifies the exact parameters and filename rules — follow that.

"Insert a cover page into this PDF"

write_pdf also supports modifying existing PDFs via an operations array (insert / delete pages). Use it for existing-PDF edits that produce a new PDF — adding a cover page, removing a section, merging in content from another file. See the write_pdf tool description for the operation shapes and parameter rules.

"Analyze this 200MB CSV"

start_process("python3 -i", timeout_ms=...) opens a Python REPL and returns a PID. interact_with_process(pid, "import pandas as pd; df = pd.read_csv('/abs/path.csv')") loads it once. Every subsequent question — df.describe(), df.groupby('col').size(), plot a chart — runs in the same already-loaded REPL. Libraries don't re-import, the dataframe doesn't re-load. The MCP itself recommends this workflow for any local data-file analysis.

"Run a quick Node script"

start_process("node:local", timeout_ms=...) opens a stateless Node execution mode on the MCP server itself — ES imports supported. start_process opens the runner; each piece of JS is sent via interact_with_process(pid, "<your JS here>") and runs independently (no shared state between calls). Good for one-shot transformations where keeping a long-lived REPL alive isn't worth it. Don't try to put code into the start_process command argument — only the runner type (node:local) goes there.

"Explain this codebase"

list_directory(path=repo_root, depth=3) for shape. start_search(pattern="export ", path=repo_root, searchType="content") to find the public surface. read_multiple_files(paths=[entrypoints]) for the actual code. The agent can keep narrowing without re-asking the user where to look.

"Organize my Downloads folder"

Resolve the path to absolute first (e.g., /Users/<user>/Downloads, not ~/Downloads). Then list_directory(path="/Users/<user>/Downloads", depth=1) to see what's there. start_search(pattern="*.pdf", path="/Users/<user>/Downloads", searchType="files") and similar for other types. create_directory for new folders. move_file per item. Preview the move plan before executing destructive ops.

"Onboard me — what was happening last session?"

get_recent_tool_calls(maxResults=200) returns recent activity with arguments and outputs. list_sessions shows still-running terminal sessions. list_searches shows in-flight searches. list_processes shows what's still alive. Together they reconstruct the work without asking the user to recap.

"Why isn't the REPL responding?"

list_sessions — if Blocked: true, the REPL is waiting for input rather than hung. read_process_output(pid, offset=-100) to see what it last printed (often a prompt). interact_with_process(pid, "<the input it's waiting for>\n") unblocks it.

Core tool inventory

Grouped index of the tools an agent reaches for most often. Not exhaustive — the MCP exposes additional config / diagnostics / feedback tools beyond this list. Detailed parameters and return shapes for every tool are in the MCP's own tool descriptions.

Process / shell: start_process, interact_with_process, read_process_output, list_processes, list_sessions, kill_process, force_terminate
Files (read/write): read_file, read_multiple_files, write_file, edit_block, write_pdf
Filesystem: list_directory, get_file_info, move_file, create_directory
Search: start_search, get_more_search_results, list_searches, stop_search
Diagnostics / config: get_recent_tool_calls, get_config

Conventions

Prefer absolute paths. Relative paths may fail depending on the working directory, and tilde paths (~/...) may not expand in all contexts. Absolute paths are the most reliable; pass them whenever you can.

Allowed-directory scope. File operations only work inside the user's configured allowedDirectories. Expect [DENIED] markers in list_directory output and rejections from read_file / write_file when the path is out of scope. Surface the rejected path to the user — don't retry.

When running on macOS: default shell is zsh. Use python3 not python. Some GNU tools have prefixed names (gsed for GNU sed). brew is the typical package manager. open opens files / apps from the terminal, mdfind is the fastest path to exact-filename search via Spotlight. Detect the host platform via get_config (or by inspecting process.platform / uname from a shell) before assuming any of the above — Windows and Linux hosts behave differently.

Pagination. Long outputs (file reads, process output, search results) all support offset and length. Negative offsets read from the end (tail mode). Use these instead of dumping huge results into context.

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs network access, Needs Python, Needs Node.js

Security

What our scanner noticed· Low risk

Phrasing that asks for actions without confirmation
Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Cline

Publisher

Cline (Official)

Source

cline/skills · skills/desktop-commander-overview · commit 2637846

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LICENSE (added by AutoGineer from LICENSE)
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2026-11-09

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