# Concept Tracker

> Use this tool when you need to efficiently organize and retrieve technical concepts from AI coding conversations. The Concept Tracker automatically extracts and categorizes key concepts, linking them to specific code locations, to solve problems of knowledge fragmentation and facilitate quick reference. It takes in coding conversations as input and outputs a searchable knowledge base with hierarchical categories.

Canonical page: https://skillsregistry.net/skills/liwengggou-mcp  
JSON: https://api.skillsregistry.net/v1/skills/liwengggou-mcp

## Description

Automatically extracts technical concepts from AI coding conversations, organizes them into a searchable knowledge base with hierarchy and categories, and links them to specific locations in your codebase.

## Trust

- **Trust score (0–1):** 0.72
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ffakvshwb4)
- **Repository:** <https://github.com/liwengggou/mcp>

## 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": "liwengggou-mcp"
    }
  }
}
```

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