Skip to content
verify mcp Beta VerifyMCP is currently in beta. If you notice any issues, get in touch and we’ll put it right.

io.github.neogeweb3/code-health-suite

PYPI · CODE-HEALTH-SUITE · SCANNED SEP 20

16 engines, 28 MCP tools for Python code quality. Zero external dependencies.

Available components

0 this week 78 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security100
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
  • No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency32
Schema Quality & AI Usability78
  • AI-judged instruction clarity (excellent).Pass
  • Tool/resource definitions use about 2159 tokens (~77/item across 28 items; 28 tools + 0 resources), lean.Pass
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management90
  • Stability observed for 27 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 28 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 28 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities20
  • Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. See how to fix → Fail
Install

How do I install the io.github.neogeweb3/code-health-suite MCP server?

io.github.neogeweb3/code-health-suite runs locally as a PyPI package, launched with uvx code-health-suite. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

pypi · code-health-suite

# add to Claude Code
claude mcp add neogeweb3-code-health-suite -- uvx code-health-suite
// .cursor/mcp.json
{
  "mcpServers": {
    "neogeweb3-code-health-suite": {
      "command": "uvx",
      "args": [
        "code-health-suite"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "neogeweb3-code-health-suite": {
      "command": "uvx",
      "args": [
        "code-health-suite"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add neogeweb3-code-health-suite -- uvx code-health-suite
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "neogeweb3-code-health-suite": {
      "type": "local",
      "command": [
        "uvx",
        "code-health-suite"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add neogeweb3-code-health-suite --command uvx --arg code-health-suite
# ~/.hermes/config.yaml
mcp_servers:
  neogeweb3-code-health-suite:
    command: "uvx"
    args: ["code-health-suite"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "neogeweb3-code-health-suite": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "code-health-suite"
      ]
    }
  }
}
# add to Vellum
assistant mcp add neogeweb3-code-health-suite -t stdio -c uvx -a code-health-suite
// mcp.json
{
  "mcpServers": {
    "neogeweb3-code-health-suite": {
      "command": "uvx",
      "args": [
        "code-health-suite"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 20 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.

  • 18 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.

  • 17 Sept 26 −3
    • Stability: pass → 0.80 functional
  • 16 Sept 26 0
    • Stability: 0.97 → pass security
  • 15 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

  • 13 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.

  • 11 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.

  • 10 Sept 26 −3
    • Stability: pass → 0.80 functional
Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 20 Sept 2026 · Analysed pypi/code-health-suite@0.8.1

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem pypi

Background: How many MCP packages publish verified provenance →

Install scripts 1 script
Hook Tier Command
build_backend allowlisted hatchling.build

Background: Why install scripts are a supply-chain risk →

Dependencies 0 packages
Packages resolved 0
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 28 exposed · ~2,159 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
analyze_change_impact ~99

Analyze the ripple effect of changing specific files. Shows direct dependents, transitive impact, affected tests, and an impact score (fraction of project affected). Use before refactoring to understand blast radius.

NameTypeReqDescription
changed_filesarrayyesList of file paths (relative to root) that are being changed.
max_depthintegerMax transitive dependency depth (default: 10).
pathstringyesProject root directory.

No output schema declared.

No examples provided.

analyze_complexity ~109

Analyze Python code complexity for a file or directory. Returns per-function metrics: cyclomatic complexity (McCabe), cognitive complexity, nesting depth, function length, and letter grades (A-F).

NameTypeReqDescription
pathstringyesFile or directory path to analyze.
sort_bystringSort metric (default: complexity).
thresholdintegerCyclomatic complexity threshold (default: 10).
topintegerReturn only top N functions by complexity. 0 = all.

No output schema declared.

No examples provided.

analyze_coupling ~63

Analyze module coupling metrics: afferent coupling (Ca), efferent coupling (Ce), instability (Ce/(Ca+Ce)), and hub scores. Identifies tightly-coupled modules that may resist change.

NameTypeReqDescription
pathstringyesProject root directory.

No output schema declared.

No examples provided.

analyze_imports ~55

Analyze Python import dependency graph. Returns module metrics, circular dependencies (cycles), orphan modules, hub modules, and instability scores. Use to understand project architecture.

NameTypeReqDescription
pathstringyesRoot directory of the Python project to analyze.

No output schema declared.

No examples provided.

analyze_test_quality ~80

Analyze test suite quality: assertion density, test length, naming conventions, magic numbers, and more. Returns per-file and per-test metrics with a quality score (0-100) and grade.

NameTypeReqDescription
max_lengthintegerMax test function length before flagging (default: 50).
pathstringyesRoot directory containing test files.

No output schema declared.

No examples provided.

analyze_type_coverage ~54

Analyze Python type annotation coverage: function signatures, parameters, return types, Any usage, and type: ignore comments. Returns per-file metrics and coverage percentages.

NameTypeReqDescription
pathstringyesFile or directory path to analyze.

No output schema declared.

No examples provided.

audit_dependencies ~63

Audit Python project dependencies for outdated packages and known vulnerabilities. Reads requirements.txt and/or pyproject.toml. Returns per-dependency status, latest versions, and CVE/vulnerability details.

NameTypeReqDescription
pathstringyesProject root directory containing requirements.txt or pyproject.toml.

No output schema declared.

No examples provided.

audit_docstrings ~62

Audit Python docstring coverage and quality. Checks public functions, methods, classes, and modules for missing or low-quality docstrings. Returns per-entity coverage, missing docstrings, and quality issues.

NameTypeReqDescription
pathstringyesFile or directory path to audit.

No output schema declared.

No examples provided.

audit_env_vars ~59

Audit environment variable usage: find undefined vars referenced in code, unused vars in .env files, secrets in templates, and missing .env.example entries. Supports Python, JavaScript, and shell scripts.

NameTypeReqDescription
pathstringyesProject root directory.

No output schema declared.

No examples provided.

audit_git_commits ~153

Audit recent git commits in a repository. Extracts changed files and runs static analysis (security scan, complexity) on each commit. Returns per-commit grades, security findings, and complexity violations.

NameTypeReqDescription
authorstringFilter commits by author name.
commitsintegerNumber of recent commits to audit (default: 10).
repostringyesPath to the git repository to audit.
severitystringMinimum security finding severity (default: low).
sincestringAudit commits since date (e.g., '3 days ago', '2026-03-01').
thresholdintegerComplexity threshold for flagging functions (default: 10).

No output schema declared.

No examples provided.

check_naming ~66

Check Python naming conventions (PEP 8). Detects violations: functions/methods must be snake_case, classes must be CamelCase, constants must be UPPER_SNAKE_CASE. Returns violations with suggestions.

NameTypeReqDescription
pathstringyesFile or directory path to check.

No output schema declared.

No examples provided.

detect_bugs ~154

Detect common Python semantic bugs using AST analysis. Finds 8 categories: missing f-strings, mutable class variables, late-binding closures, call-expression defaults (datetime.now()), mutable default arguments, assert-on-tuple, unreachable code, and unreachable exception handlers. Every finding indicates a likely real bug, not a style violation.

NameTypeReqDescription
min_severitystringMinimum severity to report (default: info).
pathstringyesFile or directory path to scan.
rulesarrayFilter by specific rules. Options: missing-fstring, mutable-class-var, late-binding-closure, call-default, mutable-default-arg, assert-tuple, unreachable-code, unreachable-except. Omit for all rules.

No output schema declared.

No examples provided.

find_clones ~114

Detect code clones (duplicated code blocks) in a Python project. Finds Type-1 (exact), Type-2 (renamed), and Type-3 (near-miss) clones. Returns clone pairs with similarity scores and cluster analysis.

NameTypeReqDescription
min_linesintegerMinimum function length to consider (default: 5).
pathstringyesDirectory path to scan for clones.
thresholdnumberSimilarity threshold 0.0-1.0 (default: 0.8).

No output schema declared.

No examples provided.

find_dead_code ~77

Detect unused imports, functions, variables, and arguments in Python code. Supports cross-module analysis to reduce false positives.

NameTypeReqDescription
categorystringFilter by category. Omit for all categories.
min_severitystringMinimum severity level (default: info).
pathstringyesFile or directory path to scan.

No output schema declared.

No examples provided.

find_hotspots ~106

Find code hotspots — files with high git churn AND high complexity. These are the riskiest files in a project: frequently changed AND hard to understand. Requires a git repository. Returns hotspot scores, risk levels, and churn/complexity breakdown.

NameTypeReqDescription
pathstringyesGit repository root path.
since_daysintegerLook back N days for churn data (default: 180).
topintegerReturn top N hotspots (default: 20).

No output schema declared.

No examples provided.

full_health_check ~105

Run all analyses (complexity + dead code + security + imports + clones + test quality + type coverage + env audit + naming + TODO debt + bug detection + docstring coverage) on a Python project and return a combined health report with scores, grades, and top issues. Note: hotspot, dependency, and change impact require additional context (git repo, requirements files, changed files) so are excluded from this scan.

NameTypeReqDescription
pathstringyesDirectory path to analyze.

No output schema declared.

No examples provided.

get_bug_score ~64

Get a bug detection health score (0-100) with grade (A-F), bug profile classification (clean/fstring_heavy/closure_heavy/etc.), and breakdown by rule and severity. Quick bug health check.

NameTypeReqDescription
pathstringyesDirectory path to scan.

No output schema declared.

No examples provided.

get_complexity_score ~52

Get an overall complexity health score (0-100) with letter grade (A-F), complexity profile classification, and top offenders. Quick project health check.

NameTypeReqDescription
pathstringyesDirectory path to analyze.

No output schema declared.

No examples provided.

get_docstring_score ~57

Get a docstring coverage health score (0-100) with grade. Measures what percentage of public entities have docstrings and penalizes low-quality docstrings. Shows worst files.

NameTypeReqDescription
pathstringyesDirectory path to audit.

No output schema declared.

No examples provided.

get_git_audit_score ~69

Get a quick overall grade and score for recent commits in a repo. Returns the aggregate score, grade, commit count, and security summary.

NameTypeReqDescription
commitsintegerNumber of recent commits to audit (default: 10).
repostringyesPath to the git repository.

No output schema declared.

No examples provided.

get_hotspot_score ~53

Get overall hotspot health score (0-100) with grade. Measures concentration of risk (churn x complexity). Lower scores indicate more hotspots that need attention.

NameTypeReqDescription
pathstringyesGit repository root path.

No output schema declared.

No examples provided.

get_import_health ~54

Get an import graph health score (0-100) with grade. Penalizes circular dependencies, orphan modules, unstable modules, and hub concentration. Quick architecture health check.

NameTypeReqDescription
pathstringyesRoot directory to analyze.

No output schema declared.

No examples provided.

get_naming_score ~59

Get a naming convention health score (0-100) with grade. Measures PEP 8 naming compliance: snake_case functions, CamelCase classes, UPPER_SNAKE_CASE constants.

NameTypeReqDescription
pathstringyesDirectory path to check.

No output schema declared.

No examples provided.

get_security_score ~46

Get an overall security health score (0-100) with grade, profile, and top vulnerability rules. Quick security posture assessment.

NameTypeReqDescription
pathstringyesDirectory path to scan.

No output schema declared.

No examples provided.

get_todo_score ~52

Get a technical debt health score (0-100) with grade based on density and severity of TODO/FIXME/HACK markers. Shows hotspot files.

NameTypeReqDescription
pathstringyesDirectory path to scan.

No output schema declared.

No examples provided.

get_type_score ~49

Get overall type coverage health score (0-100) with grade. Measures annotation completeness, Any usage, and type: ignore density.

NameTypeReqDescription
pathstringyesFile or directory path to analyze.

No output schema declared.

No examples provided.

scan_todos ~128

Scan source code for technical debt markers: TODO, FIXME, HACK, XXX, BUG, NOTE, OPTIMIZE, REFACTOR comments. Returns items with file, line, tag, severity, and message. Optionally enriches with git blame metadata.

NameTypeReqDescription
blamebooleanEnrich with git blame metadata (author, date). Slower.
pathstringyesFile or directory path to scan.
severitystringFilter by minimum severity level.
tagstringFilter by specific tag (e.g., TODO, FIXME, HACK).

No output schema declared.

No examples provided.

security_scan ~57

Scan Python code for security vulnerabilities: command injection, SQL injection, path traversal, hardcoded secrets, unsafe deserialization, XSS, and more. Maps findings to CWE identifiers.

NameTypeReqDescription
pathstringyesFile or directory path to scan.

No output schema declared.

No examples provided.

Common questions

What is the io.github.neogeweb3/code-health-suite MCP server?

io.github.neogeweb3/code-health-suite is an MCP server listed in the public MCP registry as io.github.neogeweb3/code-health-suite. 16 engines, 28 MCP tools for Python code quality. Zero external dependencies. This page covers its PyPI package (code-health-suite).

Is the io.github.neogeweb3/code-health-suite MCP server safe to use?

io.github.neogeweb3/code-health-suite scores 78 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the io.github.neogeweb3/code-health-suite MCP server expose?

io.github.neogeweb3/code-health-suite exposes 28 tools: analyze_complexity, get_complexity_score, find_dead_code, security_scan, get_security_score, and 23 more. Their descriptions and schemas cost roughly 2,159 tokens of context every time the server is loaded.

Is the io.github.neogeweb3/code-health-suite MCP server still maintained?

io.github.neogeweb3/code-health-suite is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.