Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Critical Path Method scheduling and lock-aware parallel cohorts for MCP agents.
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.
필요한 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": {
"cpm-planner": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/cpm-planner:0.5.0"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add cpm-planner -- docker run -i --rm ghcr.io/praxec/cpm-planner:0.5.0프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"cpm-planner": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/cpm-planner:0.5.0"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"cpm-planner": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/cpm-planner:0.5.0"
]
}
}
}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.
이 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
레지스트리 이름이 GitHub 계정 praxec 기준으로 확인되었고, 이 계정이 저장소를 소유하고 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 1개를 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(0.5.0)은 11일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Docker도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Rystic
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.
Start, seed, clock, inspect and diff Rystic API simulators from your agent.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
cpm-planner is a Critical Path Method (CPM) planner for agent work, exposed as an MCP server. You submit a task graph and it computes the schedule: earliest and latest start and finish, slack, the critical path and the bottleneck tasks that gate completion. It then leases lock-aware cohorts of ready deliverables with disjoint file sets, so several workers can run in parallel without colliding. Plans can live in the repository as plan-as-code files with forkable, comparable variants; read-only tools lint, level against resource capacities and run Monte Carlo risk; earned-value tools track PV, EV, AC, SPI and CPI against a frozen baseline; and an optional AI review proposes verified schedule improvements. Any MCP client (Claude Code, Cursor, VS Code, Codex, a custom orchestrator, or a praxec workflow) drives it over stdio. It is a standalone tool with no dependency on praxec.
Prebuilt packages are published for Linux, macOS and Windows on x86_64 and ARM64.
The installers resolve your OS and CPU and download the matching archive. They verify its SHA-256 against the release's `checksums.sha256` before installing, then atomically replace the binary in a user-local directory. A checksum mismatch aborts with a non-zero exit and installs nothing. Re-running the installer upgrades in place.
# Linux / macOS -> ~/.local/bin/cpm-planner
curl -fsSL https://github.com/praxec/cpm-planner/releases/latest/download/install.sh | sh
irm https://github.com/praxec/cpm-planner/releases/latest/download/install.ps1 | iex
The installer prints the absolute path it installed to. Use that path when you register the server with a GUI client.
Installer details: inspecting the script, PATH, upgrades and direct downloads
If you would rather read the script before running it, download, inspect, then run (see Pin a version for ):
# Linux / macOS
curl -fsSLO https://github.com/praxec/cpm-planner/releases/latest/download/install.sh less install.sh sh install.sh --version
# Windows
irm https://github.com/praxec/cpm-planner/releases/latest/download/install.ps1 -OutFile install.ps1 Get-Content install.ps1 .\install.ps1 -Version
PATH. If the install directory is not on your PATH, the installer prints the exact line to add. Pass --add-to-path (-AddToPath on Windows) to have it do that for you, user-level only and never with sudo.
On Linux and macOS it appends the line only if it is not already there, to:
~/.zshrc for zsh;~/.bash_profile if it exists, else ~/.bashrc, for bash;~/.profile for other shells.For fish it prints fish_add_path for you to run instead of writing a file.
Downloads. The installers only accept https:// download URLs.
Upgrades. After upgrading, restart your MCP client so it launches the new binary. On Windows the old exe is renamed to cpm-planner.exe.old and removed on the next run.
Direct downloads. You can also download an archive yourself and check it against checksums.sha256; a machine-readable release-manifest.json is published too. All assets are at https://github.com/praxec/cpm-planner/releases/latest.
| Platform | Asset |
|---|---|
| Linux x86_64 | cpm-planner-x86_64-unknown-linux-gnu.tar.gz |
| Linux ARM64 | cpm-planner-aarch64-unknown-linux-gnu.tar.gz |
| macOS x86_64 | cpm-planner-x86_64-apple-darwin.tar.gz |
| macOS Apple Silicon | cpm-planner-aarch64-apple-darwin.tar.gz |
| Windows x86_64 | cpm-planner-x86_64-pc-windows-msvc.zip |
| Windows ARM64 | cpm-planner-aarch64-pc-windows-msvc.zip |
In the commands in this README, is a release tag such as v0.2.0. Pick one from the releases page.
# Linux / macOS
curl -fsSL https://github.com/praxec/cpm-planner/releases/latest/download/install.sh | sh -s -- --version
$env:PRAXEC_VERSION = ' '; irm https://github.com/praxec/cpm-planner/releases/latest/download/install.ps1 | iex
& ([scriptblock]::Create((irm https://github.com/praxec/cpm-planner/releases/latest/download/install.ps1))) -Version
With Node 18 or later, install the cpm-planner command from npm:
npm install -g @matthew-cochran/cpm
cpm-planner --version
The package is a small launcher. It downloads the release binary for your platform, verifies its checksum and caches it, during install or, where npm skips install scripts, on first run. The package version is the release version, so npm install -g @matthew-cochran/cpm@0.2.0 pins one. To run it without installing, use npx -y @matthew-cochran/cpm. For details and environment variables, see npm/README.md.
Build and install a tagged release with Cargo (Rust 1.99 or newer):
cargo install --git https://github.com/praxec/cpm-planner --tag <version> --locked
The crates.io listing lags behind the GitHub releases until the next cargo publish, so cargo install cpm-planner does not give you the current version yet. Install from the tag as above.
docker pull ghcr.io/praxec/cpm-planner
docker run -i --rm -v cpm-planner-data:/data ghcr.io/praxec/cpm-planner
-i keeps stdin open for the stdio transport.
The image sets CPM_PLANNER_DB=/data/cpm-planner.db and declares /data as a volume owned by the unprivileged app user, so a named volume persists plan state across runs. For a bind mount (-v "$PWD:/data"), run as yourself so the directory is writable: --user "$(id -u):$(id -g)". Pass -e CPM_PLANNER_DB=... only to override the path.
To register the image with a client, put docker in command and the rest in args. For example, in Claude Code:
claude mcp add cpm-planner --scope user -- docker run -i --rm -v cpm-planner-data:/data ghcr.io/praxec/cpm-planner
cpm-planner --version
It prints cpm-planner . To check the MCP side without a client, run the smoke script from the repository. It performs the MCP initialize and tools/list handshake and fails if plan.submit, plan.status or plan.get is missing:
node scripts/mcp-smoke.mjs /absolute/path/to/cpm-planner
Write a plan as .cpm-planner/plans/ / .json (a PlanGraph):
plan.lint {path: ".cpm-planner/plans/checkout/main.json"} — static checks, no state written.plan.sync {path: ".cpm-planner/plans/checkout/main.json"} — register the variant and return its plan_id.plan.status {plan_id} — schedule, critical path, ready set and locks.plan.sync tracks the file by content hash; plan.status reports definition_drift when the tracked file and the stored head graph disagree.
Freeze the baseline, record progress, then read the report (earned_pct is earned in proportion under earning_rule: "weighted"; fifty_fifty credits 50% once a deliverable is in progress or has any reported earned_pct, and the default zero_hundred earns at completion):
plan.baseline {plan_id} — freeze the CPM schedule and budgets as baseline 1.plan.mark_status {plan_id, deliverable_id, caller_id, status: {"status": "in_progress"}, earned_pct: 50, actual_effort_hours: 4} — report progress and actual cost.plan.ev {plan_id} — PV, EV, AC, SV, CV, SPI, CPI, EAC and alerts.plan.snapshot {plan_id, format: "markdown"} — append the reading and export a Markdown table.A ratio with a zero denominator is null and explained in undefined; alerts (SPI_BELOW_0_9, CPI_BELOW_0_9) compare the two latest stored readings.
Any MCP client can run cpm-planner over stdio: register the cpm-planner binary as the command, or, with Node 18 or later, npx -y @matthew-cochran/cpm. For a GUI client, use the absolute path the installer printed.
Install the agent skills (/cpm-plan and friends) with cpm-planner skills install --target --user (or --project ), where is claude, codex, cursor, copilot, gemini, all, or agents-md (project only).
docs/AGENT-INSTALL.md has the per-client steps (Claude Code, Claude Desktop, Codex, Cursor, VS Code, Gemini CLI and others), env blocks, verification and troubleshooting. llms.txt indexes the docs for LLMs.
| Tool | Does | |
|---|---|---|
plan.submit | Submit a task graph; returns a plan id (idempotent on the graph + caller). A prerequisite is a deliverable id string or an object `{id, consumes?, kind?: artifact\ | interface, lag_hours?}; both forms round-trip through plan.get. A deliverable may set milestone: true (an acceptance point, zero-length unless given an estimate or duration, reported in plan.status milestones). An optional earning_rule (zero_hundred, the default: 100% only when complete; fifty_fifty: 50% once in progress or any earned_pct is reported; weighted: the reported earned_pct) sets how earned value credits partial progress and is part of the plan's identity. A deliverable's optional duration_hours (calendar time) replaces effort as its scheduled length and a prerequisite's lag_hours delays the dependent's start; effort stays the cost basis. An optional estimate {optimistic, likely, pessimistic} (0 <= optimistic <= likely <= pessimistic) is a three-point effort estimate. Scheduled-length precedence: duration_hours > estimated_effort_hours > estimate.likely > 0 for a milestone > the estimator default; Monte Carlo samples the estimate only when neither duration_hours nor estimated_effort_hours is set. Limits: at most 5000 deliverables, and every hour value (effort, duration, lag, estimate) finite and between 0 and 1000000 (INVALID_GRAPH). With name (optional project/variant, variant defaults to main`) it registers a named variant instead of an unnamed plan. |
| plan.acquire_cohort | Atomically acquire up to N ready deliverables with mutually disjoint file sets (an owned_files entry may be {path, mode: "append"}; append claims on one path may be co-leased and appear in shared_paths; a file may be owned by several deliverables only if they are ordered by prerequisites, or all claims are append); optional ttl_seconds sets the lease TTL (clamped to the server maximum); optional ids and filter.metadata target deliverables; metadata.kind = "manual" deliverables are never leased; th
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