Server data from the Official MCP Registry
Tabular data retrieval. Index CSV/Excel, query rows, aggregate. 99%+ savings vs raw file reads.
About
Tabular data retrieval. Index CSV/Excel, query rows, aggregate. 99%+ savings vs raw file reads.
Security Report
jDataMunch is a well-structured MCP server for tabular data analysis with proper input validation, no hardcoded credentials, and appropriate permission scoping. The codebase demonstrates good security practices with redaction features, parameterized SQL queries, and careful handling of sensitive data. Minor code quality findings around broad exception handling and some validation edge cases do not materially impact security. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
3 files analyzed · 11 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-jgravelle-jdatamunch-mcp": {
"args": [
"jdatamunch-mcp"
],
"command": "uvx"
}
}
}Reviews
No reviews yet
Be the first to review this server!
More Developer Tools MCP Servers
Fetch
Freeby Modelcontextprotocol · Developer Tools
Web content fetching and conversion for efficient LLM usage
Git
Freeby Modelcontextprotocol · Developer Tools
Read, search, and manipulate Git repositories programmatically
Toleno
Freeby Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
mcp-creator-python
Freeby mcp-marketplace · Developer Tools
Create, build, and publish Python MCP servers to PyPI — conversationally.
MCP Marketplace
Freeby mcp-marketplace · Developer Tools
Search and install MCP servers from inside your AI client.
MarkItDown
Freeby Microsoft · Content & Media
Convert files (PDF, Word, Excel, images, audio) to Markdown for LLM consumption