Wonderwhy-er/DesktopCommanderMCP is an MCP server that lets AI clients search and edit files, run terminal commands, and manage computer processes. It is used to give coding agents practical control over a local development environment through chat. The catalogue add-ons extend or configure this server and its agent workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/wonderwhy-er/desktopcommandermcp/knowledge-basenpx skills add wonderwhy-er/DesktopCommanderMCP --skill knowledge-basegit clone --depth 1 https://github.com/wonderwhy-er/DesktopCommanderMCPWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wonderwhy-er/desktopcommandermcp/knowledge-base)<a href="https://agentmods.dev/skills/wonderwhy-er/desktopcommandermcp/knowledge-base"><img src="https://agentmods.dev/badge/skills/wonderwhy-er/desktopcommandermcp/knowledge-base.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00112 | $0.02165 |
| Opus 5 | $0.00056 | $0.01082 |
| Sonnet 5 | $0.00022 | $0.00433 |
| Haiku 4.5 | $0.00011 | $0.00216 |
Grade A, and why
knowledge-base scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- knowledge-base — 100% identical, 0 lines differ
- knowledge-base — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge Base (Markdown, agent-readable)
A knowledge base (KB) here is a folder of Markdown files designed so any AI agent can navigate it without a vector database: the agent reads one index file, picks the relevant notes by their descriptions, and opens only those. Keep the whole KB readable and the index lean — the index is what gets loaded into context, so it must be high-signal.
Apply the rules below when creating a new KB, adding/editing notes, or doing a maintenance pass. When the user's request is ambiguous (new KB vs. add note vs. cleanup), ask which one before acting.
Core principles (the "why")
- Index-first navigation. The index is a map, not a container. An agent
reads
INDEX.md, selects notes by their one-line descriptions, then opens only those files. No note is "in" the KB unless it's registered in the index. - Atomicity. One topic per note. If a title needs an "and", it's probably two notes. Atomic notes are easier to find, link, and reuse.
- Stable IDs. Every note has a permanent ID that never changes and is never reused, so links survive renames and moves.
- Linked with reason. When two notes connect, state why (prerequisite, supports, contrasts, see-also). Connections carry as much value as the notes.
- Lean instructions. Keep
INDEX.mdinstructions short and high-signal — it competes for the agent's context budget. Bodies load on demand. - Structured for retrieval. Clear H1 title and H2/H3 sections so an agent can grab the relevant slice of a note, not the whole thing.
Folder structure (nested by topic)
knowledge-base/
INDEX.md # entry point: instructions + full note registry
topics/
<topic>/
_topic.md # topic map: what this topic covers + its notes
<slug>.md # one atomic note
assets/ # images / attachments referenced by notes
- Topic folders are short, lowercase nouns (
auth,billing,deploys). _topic.mdis the topic-level map of content (MOC): a short intro plus links to every note in that topic. It is a convenience view;INDEX.mdremains the source of truth.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 199 lines · 112 tokens per session scan A 34ca1c1fd9e6
knowledge-base is a skill published in the GitHub repository wonderwhy-er/DesktopCommanderMCP (9,486 stars, last pushed today), licensed MIT. It adds 112 tokens to every session and 2,165 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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