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Generate professional PDF reports from LLM output — cover, TOC, tables, charts, 5 themes.
Generate professional PDF reports from LLM output — cover, TOC, tables, charts, 5 themes.
This PDF report generator MCP server is well-structured with proper input validation, clear separation of concerns, and appropriate error handling. The main permission requirements (file I/O, Python subprocess execution, network access for external resources) align well with the server's stated purpose of generating professional PDF reports. A few code quality observations and minor security considerations exist but do not materially affect the security posture. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
4 files analyzed · 10 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-themoddedcube-pdf-report-generator": {
"args": [
"-y",
"@ctalasila/pdf-report-generator"
],
"command": "npx"
}
}
}From the project's GitHub README.
An MCP server that generates professional corporate PDF reports from structured JSON specs or raw LLM text output. Drop it into Claude Desktop (or any MCP client) and ask Claude to turn analysis, research, or meeting notes into a polished multi-page report complete with cover page, table of contents, executive summary, section headings, tables, and charts.
A sample output is at examples/sample_report.pdf.
Install Python dependencies:
pip install reportlab matplotlib
Add to your claude_desktop_config.json:
{
"mcpServers": {
"pdf-report": {
"command": "npx",
"args": ["-y", "pdf-report-generator"]
}
}
}
generate_reportGenerates a PDF from a full structured spec.
Minimal example input:
{
"spec": {
"metadata": {
"title": "Q3 Performance Review",
"author": "Engineering Team",
"company": "Acme Corp",
"classification": "INTERNAL"
},
"executive_summary": "Overall performance improved this quarter...",
"sections": [
{
"heading": "Infrastructure",
"body": "Uptime reached 99.94%...",
"subsections": []
}
],
"tables": [],
"charts": []
}
}
generate_report_from_textConverts raw text into a structured PDF report. Sections are auto-detected from headings.
{
"text": "# Overview\nThis quarter...\n\n# Key Findings\n...",
"title": "Q3 Summary",
"author": "Data Team",
"company": "Acme Corp",
"classification": "INTERNAL",
"theme_name": "navy"
}
list_themesReturns available color themes: default, navy, charcoal, forest, burgundy.
metadata
title* string
subtitle string
author string
date string (YYYY-MM-DD; defaults to today)
company string
department string
document_id string (e.g. RPT-2026-001)
classification string (PUBLIC | INTERNAL | CONFIDENTIAL)
logo_path string (absolute path to PNG/JPG)
page_size "letter" | "a4"
executive_summary string
sections[]
heading* string
body* string (\n\n = paragraph break)
subsections[]
heading* string
body* string
tables[]
title string
headers* string[]
rows* string[][]
after_section int (0-based section index; -1 = after exec summary)
charts[]
title string
type "bar" | "line" | "pie" | "horizontal_bar"
labels* string[]
datasets* [{label, values[]}]
after_section int
images[]
path* string (absolute path)
caption string
width_inches number
after_section int
theme
primary_color [R, G, B]
accent_color [R, G, B]
highlight_color [R, G, B]
Python not found — ensure python or python3 is on your PATH and is version 3.8+.
reportlab not installed — run pip install reportlab matplotlib.
Charts missing — matplotlib is required for charts. Install it with pip install matplotlib.
Large PDFs — complex specs with many charts can take 5–15 seconds. This is normal.
MIT
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