
Codehealth Mcp
- 1.1k installs
- 238k repo stars
- Updated August 5, 2026
- affaan-m/everything-claude-code
codehealth-mcp is a Claude Code skill that wraps the CodeScene Code Health MCP to score structural maintainability before edits, verify deltas after changes, and gate commits and PRs.
About
codehealth-mcp is a Claude Code skill that drives the CodeScene Code Health MCP server to give structural, design-level maintainability feedback for AI-assisted coding. It reviews a file before edits, checks the score delta after changes, and gates commits and pull requests against regressions. A developer uses it when reviewing code quality, refactoring, or checking whether an AI diff degraded a file. It complements lint and style skills with design-level health scores rather than replacing tests.
- Wraps the CodeScene Code Health MCP for structural maintainability scores
- Review before edits, verify score deltas after changes, gate commits and PRs
- Uses four standalone tools and a 1-10 score scale to scope how aggressively to change a file
Codehealth Mcp by the numbers
- 1,066 all-time installs (skills.sh)
- +218 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #113 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
codehealth-mcp capabilities & compatibility
Requires a CS_ACCESS_TOKEN; standalone mode's four tools do not require a paid CodeScene platform account.
- Capabilities
- code review · maintainability scoring · regression gating · refactoring
- Works with
- github
- Use cases
- code review · refactoring
What codehealth-mcp says it does
Real-time structural Code Health via CodeScene MCP — review before edits, verify score deltas after changes, gate commits and PRs.
Never mark the task done while the score is lower than when you started.
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| Installs | 1.1k |
|---|---|
| repo stars | ★ 238k |
| Last updated | August 5, 2026 |
| Repository | affaan-m/everything-claude-code ↗ |
What it does
Score a file's structural Code Health before and after edits and gate commits or PRs against maintainability regressions.
Who is it for?
Reviewing code quality, refactoring, checking whether AI changes degraded a file, and gating commits or PRs.
Skip if: Analyzing secrets, credentials, or paths you do not want analyzed, and it is not a replacement for tests and lint.
When should I use this skill?
The user asks to review code quality or refactor, before editing a hotspot, or before a commit or PR needing a maintainability safeguard.
What you get
A recorded baseline and post-change Code Health score that blocks commits and PRs when maintainability regresses.
By the numbers
- 4 standalone tools
- 1-10 Code Health score scale
- 3 score ranges (green/yellow/red)
Files
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-gateas 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.json → mcpServers):
"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
| Tool | When to use |
|---|---|
code_health_review | Full structural analysis before modifying a file |
code_health_score | Quick numeric score after each change (delta check) |
pre_commit_code_health_safeguard | Block commits that introduce Code Health regressions |
analyze_change_set | Branch-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)
| Range | Meaning | Agent behavior |
|---|---|---|
| 9.0–10.0 | Green — healthy | Safer to extend; still prefer vertical slices |
| 4.0–8.9 | Yellow — debt | Tread carefully; no drive-by refactors |
| 1.0–3.9 | Red — severe debt | Narrow 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_setPairing with ECC
| ECC skill / flow | Code Health MCP role |
|---|---|
coding-standards | Style/naming; Code Health = structure/complexity |
plankton-code-quality | Write-time lint/format; Code Health = pre/post edit structural gate |
verification-loop / /quality-gate | Add structural regression check before "done" |
security-review | Security vs maintainability — use both when relevant |
tdd-workflow | Tests 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 conventionsplankton-code-quality— write-time lint/format hooksverification-loop— build/test/lint gatetdd-workflow— test-first developmentsecurity-review— security checklistdocumentation-lookup— library docs via Context7 (orthogonal)
Related skills
FAQ
What credentials does it need?
No bundled token; you set CS_ACCESS_TOKEN yourself, and standalone mode does not require a paid CodeScene platform account for the four tools.
What happens if the MCP is unavailable?
Do not invent scores; tell the user the check was skipped and prefer lint, tests, and the verification loop for gating.