CodeClone

Name: CodeClone
Author: orenlab

by orenlabversion 2.0.3i★ –iRuns on your computer

Registry nameio.github.orenlab/codeclone

Install

Overview

Description from the maker (original English)

A structural review layer for Python — baseline-aware, deterministic, built for CI and AI 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

PyPIPython’s uv installed (for the uvx command)

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": {
    "codeclone": {
      "command": "uvx",
      "args": [
        "codeclone",
        "--mcp",
        "--transport",
        "stdio"
      ]
    }
  }
}

Run this in your terminal

claude mcp add codeclone -- uvx codeclone --mcp --transport stdio

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "codeclone": {
      "command": "uvx",
      "args": [
        "codeclone",
        "--mcp",
        "--transport",
        "stdio"
      ]
    }
  }
}

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": {
    "codeclone": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "codeclone",
        "--mcp",
        "--transport",
        "stdio"
      ]
    }
  }
}

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account orenlab, 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 32417 servers in this category
Published to the registry more recently than 79% of the other 32417 servers in this category
Basic checks equal to or better than 100% of the other 32417 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 CodeClone 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 (2.0.3) reached the registry 9 days ago.

Which apps can use it?

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

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, FOGA node

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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.

Deterministic Structural Change Controller for AI-assisted Python development

Let agents move fast.

Keep structural change explicit, bounded, and verifiable.

[][pypi-link] [][pypi-link] [][pypi-link] [][license-link] [][discord-link]

[][tests-link] [][benchmark-link]

[!IMPORTANT]

Sections marked `2.1 alpha` require the

CodeClone 2.1 prerelease.

Everything else works with the current stable release,

CodeClone 2.0.2.

What is CodeClone?

CodeClone helps developers use AI coding agents without losing control of structural change.

Before an agent edits code, CodeClone records the intended change, maps the structural blast radius, and establishes explicit edit boundaries. After the edit, it compares the real patch with the declared scope, verifies structural regressions, and leaves an auditable review receipt.

CodeClone does not generate or rewrite source files, and it does not ask an LLM to decide whether a structural change is safe. Every finding and every gate comes from deterministic repository facts shared across agents, human reviewers, IDEs, reports, and CI.

Capability	What it provides
Canonical structural analysis	One deterministic report: clones, complexity, coupling, cohesion, dead code, module map, API inventory, coverage joins
Baseline-aware governance	Records accepted legacy debt and separates it from regressions introduced by the current change
One report, many surfaces	CLI, HTML, JSON, Markdown, SARIF, MCP, IDE integrations, and GitHub Actions from one canonical payload
Structural Change Controller — `2.1 alpha`	Intent-first change control, blast radius, explicit edit boundaries, patch verification, and review receipts
Live Implementation Context — `2.1 alpha`	Real-time structural and call-graph context served from the current analysis run — no stale index to maintain
Engineering Memory — `2.1 alpha`	Local, typed, evidence-linked project knowledge and reusable histories of prior controlled changes
Agent coordination — `2.1 alpha`	Conflict-safe multi-agent intents, queues, recovery, and workspace hygiene

CodeClone requires no hosted service or cloud account. Analysis state, controller state, Engineering Memory, and trajectories are stored locally.

Why intent comes before the diff

Most review tools begin after the patch already exists. CodeClone begins earlier:

task request

→ declared intent → structural blast radius → explicit boundary → actual patch → deterministic verification

Agent scope expansion can look reasonable in the final diff. A narrow task may quietly spread into shared helpers, tests, configuration, public APIs, or unrelated modules.

By the time that expansion reaches the final diff, it already looks intentional. CodeClone catches it at the declared boundary instead — by comparing what the agent said it would change with what it actually changed.

Quick start

Requires Python 3.10 or newer.

1. Analyze a repository

Run the stable release without installing anything:

uvx codeclone@latest .

Prefer a browsable report? Generate the HTML view and open it:

uvx codeclone@latest . --html --open-html-report

Once you use it regularly, install it as a local tool:

uv tool install codeclone

codeclone .

2. Record the current structural baseline

Before asking an agent to change the repository, capture the accepted state once:

codeclone . --update-baseline

git add codeclone.baseline.json git commit -m "chore: add CodeClone structural baseline"

The baseline records the structural debt that already exists. Future analysis can then separate new regressions from findings that were already present, so agents and reviewers can focus on what the current change introduced.

Updating the baseline is an explicit governance action. Do not regenerate it merely to make a failing check pass.

3. Connect your AI agent — `2.1 alpha`

Continue to Agent change control below to install the MCP control surface and wire CodeClone into Claude Code, Cursor, VS Code, Codex, or Claude Desktop.

One canonical structural report

CodeClone runs one deterministic analysis and renders the same canonical report through every supported surface.

The report covers:

function, block, and segment clones;
clone drift and duplicated branch families;
complexity, coupling, cohesion, dependency cycles, and dead code;
Module Map — a package/module dependency graph with cycle, hub, overloaded-module, and unwind-candidate views;
Guided Finding Review — a prioritized review queue with shared finding cards, filters, and progress tracking;
public API inventory and baseline-aware API break detection;
external coverage joined with structural hotspots;
deterministic structural health and review priorities.

codeclone . --json --html --md --sarif --text

How CodeClone works · Canonical report contract

Baseline-aware governance and CI

The baseline is a versioned, integrity-checked contract that records the accepted structural state of the repository.

It lets CodeClone and connected agents distinguish:

findings that already existed;
regressions introduced by the current change;
deliberate baseline updates approved by the user.

Check future changes against the committed baseline:

codeclone . --ci

Use CodeClone in GitHub Actions:

- uses: orenlab/codeclone/.github/actions/codeclone@v2

with: fail-on-new: "true" sarif: "true" pr-comment: "true"

CI can reject newly introduced clones, metric regressions, API breaks, and coverage regressions without requiring the existing repository to be clean first.

Baseline contract · CI integration and quality gates

How CodeClone differs

Linters check style and correctness file by file. Clone detectors report duplication and stop there. Hosted review bots ask a model for an opinion about a finished diff.

CodeClone combines CFG-based clone detection, multi-metric baseline governance, and a read-only MCP control surface in one local-first, open-source package — and applies them before the edit happens, not only after. Structural facts are computed deterministically, so the same input always produces the same verdict, in the terminal, in CI, and inside your agent's loop.

Agent change control — `2.1 alpha`

Install the MCP control surface

uv tool install --prerelease allow "codeclone[mcp]"

codeclone-mcp --transport stdio

The server exposes 38 MCP tools covering analysis, change control, blast radius, memory, and diagnostics. Responses are built for agent loops: deterministic next_tool guidance, token-budget-aware payloads, and replies that keep mandatory control facts inline while linking full evidence for drill-down.

Before gating agents or CI, confirm [tool.codeclone] and local gitignore hygiene:

codeclone setup status

codeclone setup plan codeclone setup apply # or: codeclone setup wizard

See Repository setup and readiness.

Wire it into your client

Client	Setup
VS Code	Extension setup
Cursor	Plugin and skills
Claude Code	Plugin setup
Codex	Plugin setup
Claude Desktop	Bundle setup

Every client uses the same MCP interface and the same canonical structural facts.

The controlled-change workflow

For an agent, the normal workflow is:

analyze → start → edit → finish

Analyze. CodeClone builds one canonical structural report for the repository and compares it with the accepted baseline.

Start. start_controlled_change:

records the agent's intent;
maps structural blast radius;
separates editable paths from review context and do-not-touch boundaries;
exposes the regression budget relative to the accepted baseline;
returns the authoritative edit_allowed result.

Edit. The agent writes the code. CodeClone does not generate or rewrite source files. Where the host supports hooks, integrations can stop edits unless edit_allowed=true. While editing, the agent stays oriented through Live Implementation Context instead of rediscovering the repository with broad searches.

Finish. finish_controlled_change:

resolves the actual changed files;
checks declared scope against the real patch;
verifies structural changes;
validates optional review claims;
records Patch Trail evidence;
produces an auditable review receipt.

If the patch crosses the declared boundary or introduces regressions beyond the budget, verification fails — and the receipt records exactly where and why. The result is not an AI opinion about the patch. It is a deterministic comparison between declared intent, repository structure, the accepted baseline, and the actual change.

Read the Structural Change Controller guide

Live Implementation Context

get_implementation_context serves the agent bounded, task-scoped context directly from the current analysis run:

struct

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

CodeClone

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

FOGA node

README from the maker

What is CodeClone?

Why intent comes before the diff

Quick start

1. Analyze a repository

2. Record the current structural baseline

3. Connect your AI agent — 2.1 alpha

One canonical structural report

Baseline-aware governance and CI

How CodeClone differs

Agent change control — 2.1 alpha

Install the MCP control surface

Wire it into your client

The controlled-change workflow

Live Implementation Context

3. Connect your AI agent — `2.1 alpha`

Agent change control — `2.1 alpha`