# distill-mcp-v2

> Use this tool when you need to optimize Large Language Model (LLM) context windows and compress massive AI-agent payloads without losing critical semantic information. It solves problems related to network dependency and performance issues in LLM processing, providing a high-performance and dependency-free solution. The tool takes in LLM context windows and AI-agent payloads as input and outputs compressed and analyzed data, making it ideal for use cases involving large-scale language model optimization.

Canonical page: https://skillsregistry.net/skills/yatinkoul-distill-mcp-v2  
JSON: https://api.skillsregistry.net/v1/skills/yatinkoul-distill-mcp-v2

## Description

distill-mcp-v2 is a high-performance, network-dependency-free Python FastMCP server designed to aggressively optimize Large Language Model (LLM) context windows. It provides specialized tools for compressing and analyzing massive AI-agent payloads without losing critical semantic information.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ki59yn7oaa)
- **Repository:** <https://github.com/yatinkoul/distill-mcp-v2>

## 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": "yatinkoul-distill-mcp-v2"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/yatinkoul-distill-mcp-v2` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/yatinkoul-distill-mcp-v2/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