# JCR Journal Partition MCP Server

> Use this tool when you need to analyze and compare scientific journals, or verify their credibility. It provides access to journal partition tables, impact factors, and warning lists from reputable databases, enabling searching, comparison, and trend analysis. Ideal for researchers, academics, and authors seeking to evaluate journal quality and suitability for publication.

Canonical page: https://skillsregistry.net/skills/yosh3289-jcr-mcp  
JSON: https://api.skillsregistry.net/v1/skills/yosh3289-jcr-mcp

## Description

Provides access to journal partition tables, impact factors, and warning lists from Chinese Academy of Sciences and JCR databases. Enables searching, comparing journals, analyzing partition trends, and checking journal warning status across multiple years.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/km1sgdttu3)
- **Repository:** <https://github.com/yosh3289/jcr_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": "yosh3289-jcr-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/yosh3289-jcr-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/yosh3289-jcr-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