Re:PortFlow

npm version License: MIT

An MCP (Model Context Protocol) server that turns your ReportFlow templates into PDF reports — invoices, contracts, statements, anything you've designed — straight from Claude or any other MCP-compatible AI agent.

What it does

• Generate PDFs from natural-language requests like "create an invoice for Acme Corp totalling $300"
• Expose your ReportFlow designs and their parameter schemas directly to the AI as MCP Resources
• Bulk-generate many PDFs and download them as a single ZIP
• Save outputs to whichever workspace folder the user is currently in (Claude Desktop / Claude Code / Cursor / VS Code all supported)

Setup

Claude Desktop / Claude Code / Cursor

Add the following to your config file (.mcp.json, claude_desktop_config.json, ~/.cursor/mcp.json, etc.):

{
  "mcpServers": {
    "reportflow": {
      "command": "npx",
      "args": ["-y", "reportflow-mcp"]
    }
  }
}

That's the whole setup. No env vars, no API keys, no secrets to manage.

VS Code (MCP-enabled builds)

Same JSON in .vscode/mcp.json.

Requirements

• Node.js 18+ (auto-fetched by npx)
• A local environment with a browser (only required during the first login)
• A ReportFlow account

Usage

1. First-run authentication

After reloading the MCP client, ask the AI:

Authenticate with ReportFlow

A browser window opens. Sign in → pick a workspace → consent, and you're done. Tokens are stored in your OS keychain (macOS Keychain / Windows Credential Manager / Linux libsecret) and refreshed automatically.

2. Generate a PDF

Natural language (easiest)

Using the invoice template, create a PDF for Acme Corp totalling $330.

The AI will look up the template via list_templates, fetch its parameter schema with get_design_parameters, fill in the values, and call generate_pdf_sync — returning a local file path.

Slash commands

Command	Purpose
/generate_pdf	Step-by-step recipe for a single PDF
/generate_pdfs	Recipe for batch PDF generation
/reportflow_help	Quick feature tour

3. Where files are saved

Output location is resolved in this order:

1. Explicit instruction from the user (e.g. "save to my Desktop")
2. The currently-open workspace root (Claude Code / Cursor / VS Code)
3. The OS temp directory as fallback

Reference

Tools (called by the AI)

Tool	Purpose
authenticate	First-time / re-authentication
list_templates	List available designs
get_design_parameters	Fetch the parameter schema for a design
generate_pdf_sync / _async	Generate one PDF (sync returns path; async returns request ID)
generate_pdfs_sync / _async	Generate many PDFs (returns a ZIP)
download_file / download_zip	Download artifacts produced by async tools
suggest_params	Translate a natural-language brief into a params JSON via MCP Sampling (requires a Sampling-capable client)

Resources (attachable as AI context)

URI	Contents
reportflow://designs	List of available designs
reportflow://designs/{designId}/parameters	Parameter schema for one design
reportflow://errors	Catalog of error messages from the Content Service
reportflow://server-info	Server feature overview

Prompts (slash-command recipe cards)

/generate_pdf, /generate_pdfs, /reportflow_help — pass arguments and the AI follows the prepared workflow.

Troubleshooting

Symptom	Fix
Error containing re-authentication required	Ask the AI: "re-authenticate with ReportFlow"
npx cannot find the package	npm cache clean --force then retry
No keychain available on Linux	Falls back automatically to a chmod-0600 file under $XDG_STATE_HOME/reportflow-mcp/
Browser cannot open over SSH / remote shell	Authenticate once on a local machine; afterwards the cached token works on remote hosts

License

MIT — see LICENSE.

Links

• ReportFlow: https://re-port-flow.com
• npm: https://www.npmjs.com/package/reportflow-mcp
• Issues: https://github.com/re-port-flow/reportflow-mcp/issues