MCP Code Sanitizer
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CACHE_MAX | No | Max cache entries. | 200 |
| CACHE_TTL | No | Cache TTL in seconds. | 3600 |
| GROQ_MODEL | No | Groq model. | llama-3.3-70b-versatile |
| GROQ_API_KEY | Yes | Required. Get at console.groq.com. |
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
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_codeC | Strict analysis of a code fragment using Groq LLM. |
| compare_codeA | Compares two versions of code and evaluates whether the change is an improvement. Performs a structured diff analysis: identifies what improved, what regressed, and what changed neutrally. Returns a merge recommendation based on the findings. Useful for code review, refactoring validation, and AI-generated code verification. |
| explain_codeA | Explains what code does - step by step and clearly. Args: code: Code to explain. language: Programming language. audience: Target audience level - junior, middle, or senior. Returns: JSON with step-by-step explanation, key concepts, and gotchas. |
| generate_testsA | Generates tests for the provided code. Args: code: Code to generate tests for. language: Programming language. framework: Test framework (optional - pytest, jest, unittest, etc.). Returns: JSON with test cases, runnable test code, and coverage estimate. |
| analyze_fileA | Analyzes a whole code file from disk. Automatically detects language by file extension. Large files are split into chunks and analyzed in parallel. |
| cache_infoA | Shows cache statistics or clears the cache Args: clear: True - clears the cache, False - shows statistics. Returns: JSON with cache stats or clear result. |
| generate_reportA | Generates a beautiful HTML report from analyze_code or analyze_file results. Args: analysis_json: JSON string from analyze_code or analyze_file. output_path: Path to save the HTML file (optional). source_name: File/fragment name for the report title. Returns: JSON with fields: html, saved_to, length. |
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 7 tools
Each tool has a clearly distinct purpose: code fragment analysis, whole file analysis, cache management, code comparison, code explanation, report generation, and test generation. No overlap in functionality.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., analyze_code, generate_tests). No inconsistencies in style.
7 tools is a well-scoped set for code analysis and sanitization tasks, covering the core operations without being overwhelming or too sparse.
The tool surface covers analysis, comparison, explanation, test generation, and reporting. A minor gap is the lack of code transformation or refactoring tools, but the set is reasonable for the stated domain.