# mcp-code-shrinker

> mcp-code-shrinker — sbrejnev988-coder-mcp-code-shrinker. Use this tool when you need to analyze and optimize code projects, as it provides stratified code context and enables exact-source escalation, symbol contracts, and patching workflows with sandbox validation. It solves problems related to project analysis, code optimization, and validation, accepting code projects as input and outputting optimized and validated code. Ideal for use cases requiring in-depth code examination and refinement, such as debugging and performance enhancement.

Canonical page: https://skillsregistry.net/skills/sbrejnev988-coder-mcp-code-shrinker  
JSON: https://api.skillsregistry.net/v1/skills/sbrejnev988-coder-mcp-code-shrinker

## Description

A semantic context compiler MCP server that provides stratified L0-L3 code context with exact-source escalation, enabling project analysis, symbol contracts, exact source retrieval, and a patching workflow with sandbox validation.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wq9uyqeabc)
- **Repository:** <https://github.com/sbrejnev988-coder/mcp-code-shrinker>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "sbrejnev988-coder-mcp-code-shrinker"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sbrejnev988-coder-mcp-code-shrinker` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sbrejnev988-coder-mcp-code-shrinker/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt