Puter MCP
Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more
Critical Path Method scheduling and lock-aware parallel cohorts for MCP agents.
Pick the AI app you use, then copy the settings.
Passed 3/3 checks · Runs on your computer · ✓ Commands checked Nov 14, 2026
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
Install Docker on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
One time only; it works for every server that needs Docker
SettingsDeveloperEdit Config
{
"mcpServers": {
"cpm-planner": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/cpm-planner:0.8.0"
]
}
}
}Use Cpm Planner and tell me what you can do for me, then show me one thing✓ If Claude says it is using Cpm Planner or shows a Cpm Planner tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect Cpm Planner yet
Cpm Planner runs on your computer, but ChatGPT can only connect servers that run on the web
A · Use an app that can connect Cpm Planner
Works with Claude Code, with some setup first
Install Docker on your computer first (one time)
One time only; it works for every server that needs Docker
Mac: press Command+Space and type Terminal · Windows: open PowerShell
claude mcp add --scope user cpm-planner -- docker run -i --rm ghcr.io/praxec/cpm-planner:0.8.0You should see Cpm Planner listed as connected
Use Cpm Planner and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using Cpm Planner or shows a Cpm Planner tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
Install Docker on your computer first (one time)
One time only; it works for every server that needs Docker
Use Cpm Planner and tell me what you can do for me, then show me one thing✓ If Cursor says it is using Cpm Planner or shows a Cpm Planner tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
Install Docker on your computer first (one time)
One time only; it works for every server that needs Docker
Use Cpm Planner and tell me what you can do for me, then show me one thing✓ If VS Code says it is using Cpm Planner or shows a Cpm Planner tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.
JSON settings are under “For developers” below
Claude Code
claude mcp add --scope user cpm-planner -- docker run -i --rm ghcr.io/praxec/cpm-planner:0.8.0Claude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"cpm-planner": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/cpm-planner:0.8.0"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"cpm-planner": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/cpm-planner:0.8.0"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"cpm-planner": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/praxec/cpm-planner:0.8.0"
]
}
}
}These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Runs on your computer; the tool list appears in your AI app after you install it.
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 14, 2026
The registry name was verified with the GitHub account praxec, which owns the repo
Code last changed 2 days ago
Uses Apache-2.0
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Ask, share a tip or report that it does not work. Sorted by what people marked helpful.
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No reviews yet
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 3 of 3 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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed 2 days ago, and the latest version (0.8.0) reached the registry today.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.
In the same category: Puter MCP, XcodeBuildMCP, XcodeBuildMCP
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more
XcodeBuildMCP provides tools for Xcode project management, simulator management, and app utilities.
XcodeBuildMCP provides tools for Xcode project management, simulator management, and app utilities.
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 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