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Codehealth Mcp

  • 2 installs
  • 238k repo stars
  • Updated August 5, 2026
  • affaan-m/ecc

codehealth-mcp is a Claude Code skill that wraps the CodeScene MCP to score structural Code Health and gate commits and PRs on regressions.

About

codehealth-mcp is a Claude Code skill that connects the CodeScene Code Health MCP server to give design-level maintainability scores. It reviews a file before edits, checks the score delta after changes, and gates commits and pull requests against Code Health regressions. A developer uses it as a structural safeguard alongside lint and tests when refactoring or after large agent-written diffs. It runs the @codescene/codehealth-mcp server over stdio via npx and needs a CS_ACCESS_TOKEN.

  • Wraps the CodeScene MCP for structural Code Health scores
  • Reviews before edits and verifies score deltas after changes
  • Gates commits and PRs on Code Health regressions

Codehealth Mcp by the numbers

  • 2 all-time installs (skills.sh)
  • Ranked #947 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

codehealth-mcp capabilities & compatibility

Free standalone token for the four listed tools; requires your own CS_ACCESS_TOKEN and npx to run @codescene/codehealth-mcp.

Capabilities
code review · maintainability scoring · commit gate · refactoring
Works with
github
Use cases
code review · refactoring
Pricing
Bring your own API key
From the docs

What codehealth-mcp says it does

Real-time structural Code Health via CodeScene MCP
SKILL.md
Structural maintainability feedback for AI-assisted coding.
SKILL.md
npx skills add https://github.com/affaan-m/ecc --skill codehealth-mcp

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Listed on Skillselion
Installs2
repo stars238k
Last updatedAugust 5, 2026
Repositoryaffaan-m/ecc

What it does

Use CodeScene Code Health scores to review files and gate commits and PRs against maintainability regressions.

Who is it for?

Developers wanting a structural maintainability gate around edits, commits and PRs

Skip if: A replacement for tests or lint, or offline use when the CodeScene MCP is unavailable

When should I use this skill?

Reviewing code quality, refactoring, checking if AI changes degraded a file, or before commit or PR

What you get

Code Health scores and delta checks that block commits and PRs which degrade maintainability

  • code health review
  • score delta check
  • commit and PR maintainability gate

By the numbers

  • 4 standalone CodeScene tools
  • Code Health scale 1-10 with 3 bands
  • example improved a Flask module 4.82 to 9.1

Files

SKILL.mdMarkdownGitHub ↗

Code Health MCP (CodeScene)

Structural maintainability feedback for AI-assisted coding. Complements style/lint skills (coding-standards, plankton-code-quality) with design-level health scores and regression gates.

Upstream: codescene-oss/codescene-mcp-server Package: @codescene/codehealth-mcp (stdio via npx)

Security and boundaries

Opt-in (ECC): The codescene block in mcp-configs/mcp-servers.json is a template only. ECC plugin installs do not auto-enable bundled MCP servers. Copy the entry into your config only if you want it. You can exclude it during ECC install/sync with ECC_DISABLED_MCPS=codescene,....

Credentials: No bundled token. Set CS_ACCESS_TOKEN yourself (see getting-a-personal-access-token.md in the upstream repo). Never commit tokens to the repo.

What the tools read: When invoked, tools analyze files and git state in the local repository you point them at (paths you pass, plus branch context for analyze_change_set). They do not run by themselves. For standalone mode, follow upstream privacy docs: codescene-mcp-server README and CodeScene policies. Do not use this skill for secrets, credentials, or paths you do not want analyzed.

If the MCP is unavailable (offline, bad token, server crash): Do not invent Code Health scores. Tell the user the check was skipped. Continue only with explicit user approval. Prefer lint/tests/verification-loop for gating when MCP is down. Re-enable checks once the server connects.

When to Use

  • User asks to review code quality, refactor a file, or check if AI changes degraded maintainability
  • Before editing a hotspot, legacy module, or unfamiliar file
  • Before commit or pull request when you need a maintainability safeguard
  • After a large agent-written diff — verify Code Health did not regress
  • Pair with verification-loop, tdd-workflow, or /quality-gate as a structural check (not a replacement for tests/lint)

When to Activate

Same triggers as When to Use above — this heading is what ECC uses for skill auto-activation.

How It Works

1. Connect the MCP server

Copy the codescene entry from mcp-configs/mcp-servers.json into your harness MCP config.

Claude Code (~/.claude.jsonmcpServers):

"codescene": {
  "command": "npx",
  "args": ["-y", "@codescene/codehealth-mcp"],
  "env": {
    "CS_ACCESS_TOKEN": "YOUR_CS_ACCESS_TOKEN_HERE"
  }
}

Project-scoped: merge the same block into .mcp.json at the repo root.

Token setup is documented in the upstream repo (link above). Standalone mode does not require a paid CodeScene platform account for the four tools listed below. Restart the session and confirm the codescene server is connected before relying on scores.

2. Call standalone tools only

ToolWhen to use
code_health_reviewFull structural analysis before modifying a file
code_health_scoreQuick numeric score after each change (delta check)
pre_commit_code_health_safeguardBlock commits that introduce Code Health regressions
analyze_change_setBranch-level check before opening a PR

Do not call platform-only tools (e.g. repository-wide technical debt hotspot lists). Do not reference delta_analysis — not available on standalone.

3. Interpret scores (1–10)

RangeMeaningAgent behavior
9.0–10.0Green — healthySafer to extend; still prefer vertical slices
4.0–8.9Yellow — debtTread carefully; no drive-by refactors
1.0–3.9Red — severe debtNarrow scope only

4. Run the feedback loop

Before touching a file

1. Run code_health_review on the target path. 2. Record baseline score and listed code smells. 3. Plan the smallest change that addresses the task.

Scope by score: below 5 — minimal diff only; 5–7 — no broad refactors; above 7 — safer to refactor, still verify after each edit.

After each change

1. Run code_health_score on the same file. 2. Compare to the baseline from code_health_review. 3. If the score regressed, fix before continuing. Never mark the task done while the score is lower than when you started.

Before every commit — run pre_commit_code_health_safeguard on the repository path.

Before a PR — run analyze_change_set against the base branch (e.g. main).

Examples

Example: Flask maintainability improvement

On pallets/flask, an agent loop using only standalone tools:

1. code_health_review on a target module (baseline 4.82) 2. Targeted refactor addressing listed smells 3. code_health_score after each edit 4. pre_commit_code_health_safeguard before commit 5. analyze_change_set before PR

Result: Code Health 4.82 → 9.1 (free standalone token only).

Example: AGENTS.md enforcement block

Paste into the project AGENTS.md or CLAUDE.md:

## Code Health (CodeScene MCP)

Before modifying any file: run `code_health_review`, note score and issues.

- Score below 5: problematic range — scope changes narrowly.
- Score 5–7: warning range — no broad refactors.

After each change: run `code_health_score` to verify delta.

- If score regressed: fix before continuing; never declare done if score dropped.

Before every commit: run `pre_commit_code_health_safeguard`.

Before PR: run `analyze_change_set`.

Example: anti-patterns vs correct loop

# BAD: Edit first, check later
[large refactor without code_health_review]

# BAD: Ignore score drop
"Tests pass" → mark task done while Code Health decreased

# BAD: Broad refactor on red-score file (below 5)
Drive-by cleanup across the module

# GOOD: review → small change → score → commit safeguard → analyze_change_set

Pairing with ECC

ECC skill / flowCode Health MCP role
coding-standardsStyle/naming; Code Health = structure/complexity
plankton-code-qualityWrite-time lint/format; Code Health = pre/post edit structural gate
verification-loop / /quality-gateAdd structural regression check before "done"
security-reviewSecurity vs maintainability — use both when relevant
tdd-workflowTests pass ≠ healthy design — check score after refactors

Context tip: ECC recommends keeping MCP count low. Enable codescene when doing substantive edits; disable when not needed.

Related Skills

  • coding-standards — baseline conventions
  • plankton-code-quality — write-time lint/format hooks
  • verification-loop — build/test/lint gate
  • tdd-workflow — test-first development
  • security-review — security checklist
  • documentation-lookup — library docs via Context7 (orthogonal)

Related skills

FAQ

What does codehealth-mcp gate on?

Code Health score regressions at review, commit and pull-request time using standalone CodeScene tools.

Does codehealth-mcp need a token?

Yes. You set your own CS_ACCESS_TOKEN; no token is bundled.

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