io.github.themoddedcube/pdf-report-generator
Generate professional PDF reports from LLM output — cover, TOC, tables, charts, 5 themes.
Open source Open in the app JSON README (API)
About
Generate professional PDF reports from LLM output — cover, TOC, tables, charts, 5 themes.
Details
- Kind
- MCP servers
- Topic
- AI, RAG & memory
- Publisher
- themoddedcube
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 1.0.1
- Last push
- 2026-04-25T12:38:37Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 04:01:32
- Updated
- 2026-08-29 04:01:32
- Origin id
io.github.themoddedcube/pdf-report-generator
README
# pdf-report-generator
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`](examples/sample_report.pdf).
---
## Prerequisites
- **Node.js 18+**
- **Python 3.8+**
Install Python dependencies:
```bash
pip install reportlab matplotlib
```
---
## Claude Desktop configuration
Add to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"pdf-report": {
"command": "npx",
"args": ["-y", "pdf-report-generator"]
}
}
}
```
---
## Available tools
### `generate_report`
Generates a PDF from a full structured spec.
**Minimal example input:**
```json
{
"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_text`
Converts raw text into a structured PDF report. Sections are auto-detected from headings.
```json
{
"text": "# Overview\nThis quarter...\n\n# Key Findings\n...",
"title": "Q3 Summary",
"author": "Data Team",
"company": "Acme Corp",
"classification": "INTERNAL",
"theme_name": "navy"
}
```
---
### `list_themes`
Returns available color themes: `default`, `navy`, `charcoal`, `forest`, `burgundy`.
---
## JSON spec reference
```
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]
```
---
## Example prompts
- "Turn this analysis into a professional internal PDF report titled 'Q3 Infrastructure Review'"
- "Generate a corporate report from this research, add a bar chart for the monthly metrics"
- "Create a CONFIDENTIAL report called 'Security Audit Findings' from this text"
- "List the available report themes"
---
## Troubleshooting
**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.
---
## License
MIT