CodeHealth MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LLM_API_KEY | Yes | Your LLM API key for the analysis engine (e.g., OpenAI, Anthropic, DeepSeek). Edit .env with this key. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_dead_codeA | Analyze a codebase for dead code — functions, classes, and modules that are defined but never referenced. Returns findings with file paths, line numbers, severity, and fix suggestions. |
| detect_circular_depsA | Detect circular dependencies between modules using DFS-based cycle detection. Returns cycles with involved files and impact assessment. |
| analyze_couplingA | Analyze coupling metrics across the codebase. Identifies modules with high fan-out (too many dependencies) and tightly coupled clusters. |
| detect_architectural_driftA | Detect architectural drift — violations of intended layer boundaries (e.g., UI importing from data layer, reverse dependencies). |
| full_health_scanA | Run a complete codebase health scan: dead code, circular dependencies, coupling metrics, and architectural drift. Returns an overall health score (0-100) and prioritized findings. |
| explain_findingA | Get a detailed explanation of a specific code health finding, including why it matters, potential risks, and detailed remediation steps. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool targets a distinct analysis concern: dead code, circular deps, coupling, architectural drift, combined scan, and explanation. No overlap in purpose; even full_health_scan is clearly a superset rather than a duplicative tool.
Naming follows a strong verb_noun pattern but mixes 'analyze' and 'detect' as starting verbs, plus 'full_health_scan' and 'explain_finding' break the strict pattern slightly. Still, all names are descriptive and predictable.
Six tools are well-scoped for a code health analysis server. Each tool covers a meaningful aspect, and the full scan consolidates several, avoiding redundancy.
The server covers the core analysis surface (dead code, circular deps, coupling, architecture) plus explanation and a comprehensive scan. Minor gaps like generating reports or managing ignore lists are not essential for the apparent scope.