Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
What your agents should know about you, shared by every agent. End-to-end encrypted.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
PORT필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"decoy": {
"command": "npx",
"args": [
"-y",
"decoy-mcp-server"
],
"env": {
"PORT": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add decoy --env PORT=your-value -- npx -y decoy-mcp-server실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"decoy": {
"command": "npx",
"args": [
"-y",
"decoy-mcp-server"
],
"env": {
"PORT": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"decoy": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"decoy-mcp-server"
],
"env": {
"PORT": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
PORT env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
게시자(decoys.me)가 저장소 소유자(decoy-identity)가 아니에요. 다른 사람이 등록했을 수 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 0개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.4.0)은 4일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, OpenTakeoff
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Construction takeoff for AI agents: load plans, set scale, measure, count, export with provenance.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Your Decoy vault is what your agents should know about you, shared by every agent you connect: your memories, accounts (logins, codes, passkeys), personal info (emails, phones, cards, addresses) and Decoy addresses. Your memories, accounts and personal info are end-to-end encrypted: Decoy's servers can't read them. Mail to your Decoy addresses is encrypted as it arrives. You choose exactly what each agent can read or change. This package is the local MCP bridge to your vault, for Claude Desktop, Claude Code or any MCP client.
Agents and the vault: read before, write after. Check the vault before asking the person. Save lasting facts as new memories, sensitive ones too; if you can't save, ask once for Save. Update a memory when its fact changes, instead of adding another. Ask for only what the task needs.
End-to-end encrypted. Memories, secrets and mail are decrypted on your machine; Decoy's servers store ciphertext. Some things are plaintext to the server by design:
label and agent_label values;domain given to request_access;account_unlock with domain sends the domain only from a connection without your vault key; one that holds it finds the account on your machine and reads it by id, and so do credential_get and resolve;reason text shown in approval prompts, as the agent wrote it (a reason the bridge writes itself says "this account" and names no site);request_approval description and metadata;inbox_list sender_domain and decoy_list search, which are sent as filters;A connection without your vault key (for example "Create accounts" alone) seals an account's service name and site on your machine when it creates the account: once to your own key, and once to that connection's key, so it can read the name back. The banner on mail forwarded from that account's address is titled with the account's label. Sealing keeps the name and site from being stored readable: Decoy stores the two sealed copies as sent. For your copy the bridge seals to the public key Decoy serves for you, and it trusts that key. They leave your machine sealed or not at all: when they cannot be sealed (the connection has no key of its own, or your public key is not on file), or Decoy does not take them sealed, the account is not created and the tool says why. A rename is sealed on your machine to your own key, and your Decoy app applies it. A label is plain text to the server: never put a name you want kept private, or a secret, in a label.
Every request the bridge sends to the Decoy API it is set to carries one header that names this package and its version: X-Decoy-Client: decoy-mcp-server/1.3.1 (decoy-mcp-server/1.3.1; mode=context from a --context run). It says nothing about your machine, your client or you, and it is sent to no other host.
npx decoy-mcp-server
On first run it prints "Tap to connect Decoy:" and a link to https://decoys.me/connect; you approve it in the Decoy iOS app, and it prints "Connected to Decoy." An agent that meets an unconnected bridge says exactly that to you: "Tap to connect Decoy:" with the link on its own line, then "Connected to Decoy." once you approve, and nothing else about connecting. The connection is saved under ~/.decoy/ and reused on every later run; see Staying connected.
The bridge serves MCP over HTTP at http://localhost:3001/mcp. Then make Decoy the first step of every task.
Point a Streamable HTTP-capable MCP client at the local bridge. For clients using the mcpServers HTTP configuration format:
{
"mcpServers": { "decoy": { "type": "http", "url": "http://localhost:3001/mcp" } } }
Keeping the bridge on its latest release is part of setup: the owner approved it when they connected Decoy, so an agent updates it without asking. When a newer release is published, the bridge says so in its --context output and after one tool result per session, with the version and the command: npx -y decoy-mcp-server@latest (or your install's own update), then a restart of the bridge. The saved connection is kept. A bridge more than two minor versions behind the latest release (with latest 1.3.x, below 1.1.0) is refused with UPDATE_REQUIRED and the same command.
Run it so it updates with nobody stepping in:
npx -y decoy-mcp-server@latest. Each start runs the latest release.# /etc/systemd/system/decoy-mcp.service
[Unit] Description=Decoy MCP bridge After=network-online.target Wants=network-online.target
[Service]
User=agent Environment=DECOY_AGENT_NAME=Your agent's name Environment=DECOY_NO_BROWSER=true ExecStart=/usr/bin/env npx -y decoy-mcp-server@latest Restart=on-failure RestartSec=10
[Install] WantedBy=multi-user.target
# /etc/systemd/system/decoy-mcp-update.service
[Unit] Description=Restart the Decoy MCP bridge on its latest release
[Service] Type=oneshot ExecStart=/usr/bin/systemctl try-restart decoy-mcp.service
# /etc/systemd/system/decoy-mcp-update.timer
[Unit] Description=Restart the Decoy MCP bridge daily
[Timer] OnCalendar=daily RandomizedDelaySec=1h Persistent=true
[Install] WantedBy=timers.target
sudo systemctl daemon-reload
sudo systemctl enable --now decoy-mcp.service decoy-mcp-update.timer
@latest runs each release as it is published. To check each release yourself before it runs, pin a version instead (npx -y decoy-mcp-server@1.3.1) and move the pin when the bridge says a newer one is out.
The memory tools ship in the bridge. Start it as in Quick start, approve the connection in the Decoy app, then connect a Streamable HTTP MCP client to http://localhost:3001/mcp. A hosted agent cannot reach the user's localhost; run the bridge inside its trusted integration environment.
Memory search uses mem0's engine locally (optional dependencies, installed with the package). Its embedding model (Qdrant's bge-small-en-v1.5) is downloaded once from a pinned Hugging Face commit, checked against its SHA-256, and cached under ~/.decoy/models. Search and embeddings run on your machine. Memory text is never sent to Decoy, which stores ciphertext and which category, topic or account each memory is shared through, or to the model host. Your MCP client's model sees the memories it reads, and tags new ones through MCP sampling. Set DECOY_MEMORY_ENGINE=basic to skip the engine and the download. The engine's optional dependencies add about 300 MB and run native install scripts (better-sqlite3, onnxruntime-node); to install without them, run with npm_config_omit=optional (memory search then uses word overlap).
The default memory tools are add_memory, search_memories, get_memories, get_memory, update_memory, delete_memory, and the topic tools list_topics, read_topic, list_duplicate_topics, connect_topics, disconnect_topics, set_topic_parent and move_memories. Check the actual tools/list schema. The bridge handles encryption and keeps one user-owned store. There is no account named Memories to create and no place to pick. Saving takes memory.save (Save new memories), which the bridge asks for when it connects, together with memory.read (Read all memories) and account.create (Add accounts to Decoy). While a connection holds memory.save it reads and edits what it saved; deleting a memory takes memory.delete. Without memory.save a save answers 403 INSUFFICIENT_GRANT; ask once with request_access({"permissions":["memory.save"]}) and retry. Other memories follow memory.read / memory.edit (all, or by category or topic) and, for the memories about an account, acctmem.*.
How an agent is told to use memory:
misc only when no other category fits), and one place, chosen in this order:app_id: the account's name exactly as list_topics shows it under accounts, or its ID): order status, the plan, a renewal date, support history, how you like to use it.A memory is about an account or a topic, not both. Every save answers with where the memory landed (filed).
Sam Sample is renovating a kitchen and has an account named "Example Cabinets" with the cabinet supplier. Each fact is saved where it belongs. In the calls the memory text says "the user": that is how an agent is told to write it. These are MCP tool calls:
app_id is the account's name exactly as list_topics shows it under accounts, or its ID:add_memory({"text":"Cabinet order placed with Example Cabinets on 2026-03-02.","app_id":"Example Cabinets","categories":["milestones"]})
The result says where it landed, before anything else about its place: "filed": {"under":"account","id":" ","name":"Example Cabinets"}.
add_memory({"text":"Example Cabinets delivery is booked for the week of 2026-03-23.","app_id":"Example Cabinets","categories":["milestones"]})
add_memory({"text":"For Example Cabinets deliveries, the user asked on 2026-03-02 for a slot after 10am.","app_id":"Example Cabinets","categories":["user_preferences"]})
add_memory({"text":"On 2026-02-20 the user decided to keep the current kitchen layout, so no pipes are moved.","topic":"Kitchen renovation","topic_type":"project","topic_link":{"relation":"is renovating"},"categories":["milestones"]})
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요