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The Problem

Dead code, circular dependencies, excessive coupling, and architectural drift are invisible in day-to-day work. Static analysis tools produce noise in CI dashboards nobody checks. CodeHealth MCP brings these insights into the tools developers actually use — via the Model Context Protocol.

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What CodeHealth MCP Does

7 analysis tools, available in any MCP-compatible client:

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Where It Works

Claude Desktop Config

{
  "mcpServers": {
    "codehealth": {
      "command": "node",
      "args": ["/path/to/codehealth-mcp/mcp-server/index.js"]
    }
  }
}

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Quick Start

git clone https://github.com/icohangar-ops/codehealth-mcp.git
cd codehealth-mcp
npm install
cp .env.sample .env
# Edit .env with your LLM API key
npm start

Use in Claude Desktop

Run a full health scan on /path/to/my/repo

Find circular dependencies in the frontend

Check coupling metrics in src/services

Check MCP health on https://example.com/mcp

Remote MCP protocol health (not HTTP uptime)

A remote MCP endpoint can return HTTP 200 while initialize, tools/list, or the SSE stream fails. CodeSentinel probes the protocol itself:

• Synthetic Streamable HTTP / legacy SSE handshake (initialize + tools/list)
• Known-bad tools/call error-shape probe (alarm on HTTP 200 empty/swallowed protocol)
• Streamable HTTP diagnostic matrix with reason codes (WRONG_METHOD, WRONG_ACCEPT, MISSING_SESSION, GET_VS_POST, SESSION_STICKY_MISMATCH)
• Canonical tool-schema hash and drift alarms
• Discovery-latency metrics
• Secret scanning of tool descriptions/schemas before they enter agent context

npm test
npm run mcp:health -- https://example.com/mcp

Library: src/lib/mcp-health. Analyzer: lib/analyzers/mcp-health.js. Full write-up: docs/mcp-health.md.

Daytona sandbox scans (optional)

Set DAYTONA_API_KEY (and optionally GITHUB_TOKEN for private repos). MCP tools and Slack analysis will shallow-clone GitHub URLs in a Daytona VM and return live import-graph findings instead of demo data.

full_health_scan repo_path=https://github.com/org/repo

Use in Slack

Add the Slack app manifest, enable Agent Builder, and @CodeHealth in any channel.

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Architecture

┌──────────────────────────────────────────┐
│          MCP CLIENT (any)                │
│  Claude Desktop, Cursor, Slack, etc.     │
└──────────────────┬───────────────────────┘
                   │ MCP Protocol (stdio)
┌──────────────────▼───────────────────────┐
│         CODEHEALTH MCP SERVER            │
│                                          │
│  🔧 analyze_dead_code                    │
│  🔧 detect_circular_deps                 │
│  🔧 analyze_coupling                     │
│  🔧 detect_architectural_drift           │
│  🔧 full_health_scan                     │
│  🔧 explain_finding                      │
│  🔧 check_mcp_health                     │
│                                          │
│  ┌──────────────────────────────────┐    │
│  │       Analysis Engine            │    │
│  │  dead-code | circular-deps       │    │
│  │  coupling | drift | mcp-health   │    │
│  └──────────────────────────────────┘    │
│                                          │
│  ┌──────────────────────────────────┐    │
│  │       LLM Provider               │    │
│  │  Deepseek / OpenAI / Anthropic   │    │
│  └──────────────────────────────────┘    │
└──────────────────────────────────────────┘

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Slack Integration

CodeHealth MCP ships with a full Slack Agent Builder app featuring:

• Block Kit UI — Severity-coded findings, health scores, actionable suggestions
• Thread-based conversations — Follow-up analysis in threads
• Suggested prompts — One-click analysis triggers
• MCP server — Same tools, available everywhere

Demo Sandbox (Devpost judges)

The live demo workspace is codehealthdemo.slack.com — the CodeSentinel agent (App ID A0BEHRDN5TQ) is installed and authorized there. Mention it in any channel:

@CodeSentinel run a full health scan on https://github.com/icohangar-ops/codesentinel

Sandbox configuration:

Live agent response in the sandbox — a real @CodeSentinel mention in #general triggering a Daytona-sandboxed repo scan:

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Adding Custom Analyzers

Each analyzer follows a simple interface:

function analyze(repoInfo) {
  return {
    type: "your_analysis_type",
    findings: [
      {
        type: "finding_type",
        severity: "critical" | "warning" | "info",
        file: "path/to/file.ts",
        line: 42,
        name: "symbol_name",
        reason: "Why this is a problem",
        suggestion: "How to fix it",
      },
    ],
    stats: { /* summary metrics */ },
  };
}

Add a new analyzer in lib/analyzers/, register it in analysis-engine.js, and it's automatically available in Slack and via MCP.

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Roadmap

• Real AST analysis — ts-morph for TypeScript, tree-sitter for multi-language
• GitHub App — Automatic analysis on PRs with inline comments
• Historical trends — Track health score over time per repo
• Custom architecture rules — Define layer boundaries via config
• Team dashboards — Aggregate health in Slack Canvas

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Project Structure

codehealth-mcp/
├── app.js                    # Bolt app entry (Slack)
├── manifest.json             # Slack app manifest
├── lib/
│   ├── analysis-engine.js    # Analysis orchestrator + health score
│   ├── intent-parser.js      # NLP intent classification
│   ├── block-kit-builder.js  # Rich Slack UI
│   ├── llm-provider.js       # Multi-provider LLM
│   └── analyzers/            # dead-code, circular-deps, coupling, drift, mcp-health
├── src/lib/
│   ├── resilience/           # safeFetch / retry
│   └── mcp-health/           # handshake, silent probe, Streamable reason codes, CLI
├── mcp-server/
│   ├── index.js              # MCP server (code analyzers + check_mcp_health)
│   └── package.json
├── test/                     # handshake / silent-probe / streamable-diag / drift / secrets
└── functions/                # Slack function definitions

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Community & Registry

CodeHealth MCP is listed in the following directories:

• awesome-mcp-servers – A curated list of MCP servers.
• MCP Registry – Official registry for Model Context Protocol servers.

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License

MIT. See LICENSE.