Cpm Planner

Name: Cpm Planner
Author: praxec

by praxecversion 0.5.0i★ –iRuns on your computer

Registry nameio.github.praxec/cpm-planner

Install

Overview

Description from the maker (original English)

Critical Path Method scheduling and lock-aware parallel cohorts for MCP agents.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

DockerDocker installed

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "cpm-planner": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/praxec/cpm-planner:0.5.0"
      ]
    }
  }
}

Run this in your terminal

claude mcp add cpm-planner -- docker run -i --rm ghcr.io/praxec/cpm-planner:0.5.0

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "cpm-planner": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/praxec/cpm-planner:0.5.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "cpm-planner": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/praxec/cpm-planner:0.5.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account praxec, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32564 servers in this category
Published to the registry more recently than 76% of the other 32564 servers in this category
Basic checks equal to or better than 100% of the other 32564 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Cpm Planner safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.5.0) reached the registry 11 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Tools MCP

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

cpm-planner

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.

Install
Prebuilt binary (recommended)
Pin a version
npm
From source
Docker
Verify the install
Quickstart: plan as code
Quickstart: earned value
Use with AI agents
MCP tools
Plan-as-code workflow
Plan review (optional)
Use as a library
Praxec
Environment variables
Documentation
Contributing
License

Install

Prebuilt binary (recommended)

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

Windows (PowerShell) -> %LOCALAPPDATA%\Programs\cpm-planner\cpm-planner.exe

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`

Pin a version

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

Windows (PowerShell): the piped form cannot take parameters, so use the environment variable...

$env:PRAXEC_VERSION = ' '; irm https://github.com/praxec/cpm-planner/releases/latest/download/install.ps1 | iex

...or a script block

& ([scriptblock]::Create((irm https://github.com/praxec/cpm-planner/releases/latest/download/install.ps1))) -Version

npm

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.

From source

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

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

Verify the install

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

Quickstart: plan as code

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.

Quickstart: earned value

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.

Use with AI agents

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.

MCP tools

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

Only the beginning is shown; read the rest in the repo

Cpm Planner

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Tools MCP

README from the maker

cpm-planner

Contents

Install

Prebuilt binary (recommended)

Windows (PowerShell) -> %LOCALAPPDATA%\Programs\cpm-planner\cpm-planner.exe

Pin a version

Windows (PowerShell): the piped form cannot take parameters, so use the environment variable...

...or a script block

npm

From source

Docker

Verify the install

Quickstart: plan as code

Quickstart: earned value

Use with AI agents

MCP tools