JCR

Provides up-to-date journal partition data from ShowJCR via MCP, with tools to search, trend analysis, and journal comparisons.

python

3

GitHub Stars

python

Language

5 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "yosh3289-jcr_mcp": {
      "command": "python",
      "args": [
        "jcr_mcp_server.py"
      ]
    }
  }
}

You run a Model Context Protocol (MCP) server that serves up-to-date journal partition information from the ShowJCR data, enabling you to query journal divisions, trends, and warnings for large language model workflows. This server provides practical tools to search journals, analyze partition trends, compare journals, and check warning lists, all through MCP-compatible clients.

How to use

You interact with the server through an MCP client to perform common tasks such as searching for journals, viewing partition trends, comparing journals, and checking for warned publications. Use the available tools to retrieve current partition assignments, historical trends, and alert statuses, then present the results to your downstream applications or analysis dashboards.

How to install

Prerequisites you need before installing and running the MCP server:

Python 3.8 or newer
SQLite3
Git (optional, for cloning)

pip install -r requirements.txt

# Optional: if you clone the project, navigate to the project directory first
# git clone https://example.com/your/repo.git
# cd repo

python data_sync.py

# After syncing data, start the MCP server
python jcr_mcp_server.py

Additional setup and ongoing usage

The server supports local running via a standard Python command. Start it with the following command once dependencies are installed and data is synchronized.

python jcr_mcp_server.py

Available tools

search_journal

Search journal information such as impact factors, partitions, and alert status.

get_partition_trends

Fetch trends in partition changes for a given journal.

check_warning_journals

Query the list of journals flagged for warnings.

compare_journals

Compare multiple journals based on latest factors, partitions, and warnings.