基于ShowJCR仓库数据的Model Context Protocol (MCP) 服务器，为大语言模型提供最新的期刊分区表查询功能。
Jcr MCP MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. 基于ShowJCR仓库数据的Model Context Protocol (MCP) 服务器，为大语言模型提供最新的期刊分区表查询功能。.
Once Jcr MCP is connected, these are the calls the assistant has available:
search_journal — 搜索期刊信息，包括影响因子、分区、预警状态等get_partition_trends — 获取期刊分区变化趋势分析check_warning_journals — 查询国际期刊预警名单compare_journals — 对比多个期刊的综合信息Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Jcr MCP's toolset — search_journal, get_partition_trends, check_warning_journals and 1 more — is a fair guide to whether it matches your workflow. It is maintained by yosh3289; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| search_journal | 搜索期刊信息，包括影响因子、分区、预警状态等 |
| get_partition_trends | 获取期刊分区变化趋势分析 |
| check_warning_journals | 查询国际期刊预警名单 |
| compare_journals | 对比多个期刊的综合信息 |
{
"mcpServers": {
"jcr-partition": {
"command": "/path/to/python",
"args": ["/path/to/jcr_mcp_server.py"],
"cwd": "/path/to/project"
}
}
}Configuration as documented by the project. Restart the client after saving.
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