Re:port Flow MCP

Official display name: Re:port Flow MCP. Package and implementation identifier: reportflow-mcp. Legacy search aliases: ReportFlow MCP Server and ReportFlow.

Overview

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

Features

Generate PDFs from natural-language requests like "create an invoice for Acme Corp totalling $300"
Expose your Re:port Flow 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)

Agent Skill

Agents that should follow a procedure (not just read the protocol) use skills/re-port-flow/SKILL.md. Copy that directory into Claude Code / Codex .agents/skills or a Cursor project skill folder. PDF generation always goes to https://mcp.re-port-flow.com/mcp. The Hugging Face Space MCP (org card) is gallery-only — add it from the Space MCP badge → Add to MCP tools, not as a substitute for the product endpoint.

Setup

Re:port Flow MCP runs in two ways — pick whichever matches your client.

Remote server (claude.ai / web clients) — Streamable HTTP

Add Re:port Flow as a custom connector pointing at the hosted endpoint:

Code

https://mcp.re-port-flow.com/mcp

In Claude (claude.ai) go to Settings → Connectors → Add custom connector and paste the URL above. Authentication is handled in-app via OAuth (see Authentication) — nothing to install locally.

Local server (Claude Desktop / Claude Code / Cursor) — stdio via npx

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

config.json

{
  "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

Remote: an MCP client that supports custom HTTP connectors (e.g. claude.ai). No local install.
Local (stdio): Node.js 22+ (auto-fetched by npx) and a browser available during the first login.
A Re:port Flow account (either way).

Supported protocol revisions

Both transports (stdio / Streamable HTTP) serve two MCP protocol generations from a single endpoint:

2026-07-28 (current) — stateless per-request protocol. Modern clients discover it via server/discover; no session header, requests carry their protocol version in _meta.
2025-era revisions (2025-11-25, 2025-06-18, 2025-03-26, 2024-11-05, 2024-10-07) — classic initialize handshake, kept for backwards compatibility with existing clients (Claude Desktop, claude.ai custom connectors, Cursor, ChatGPT, n8n, …).

Version selection is automatic on both transports: modern clients probe with server/discover, legacy clients keep sending initialize — no configuration is required on either side, and existing connections keep working unchanged.

Authentication

Remote (claude.ai)

When you add the connector, Claude runs the OAuth flow for you: Sign in → pick a workspace → consent. Tokens are held by the client — there's no local keychain or browser step to manage.

Local (stdio)

After reloading the MCP client, ask the AI:

Authenticate with Re:port Flow

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), with a chmod-0600 file fallback, and are refreshed automatically.

Usage examples

Each example below is a prompt you can paste as-is; the AI picks the right tools.

1. Generate a single PDF (list → schema → generate)

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

The AI lists designs with list_templates, fetches the parameter schema with get_design_parameters, fills in the values, and calls generate_pdf_sync.

Remote: returns a download URL (fileUrl).
Local: also saves the file and returns its absolute path.

2. Batch-generate many PDFs

From the statement template, generate one PDF per customer (Acme $100, Globex $250, Initech $80) and give them to me together.

Local (stdio): generate_pdfs_sync writes a single ZIP to your workspace.
Remote: generate_pdfs_async runs the batch and returns a request id plus a download URL.

3. Async generate, then download (local)

Kick off the contract PDF in the background, then download it once it's ready.

The AI calls generate_pdf_async (returns a requestId immediately), then download_file to save the finished PDF. The batch equivalent is generate_pdfs_async → download_zip. These download tools are stdio-only; on the remote server the sync/async tools already return a fileUrl.

Tip — natural-language params: on a Sampling-capable client you can ask "draft the params for a $1,000 invoice to A社" and the AI will call suggest_params to turn the brief into a valid params object before generating.

4. Start from zero templates (gallery → copy → generate)

I don't have any templates yet — create an invoice PDF for Acme Corp.

When list_templates is empty, the AI searches the public template gallery with search_gallery_templates, shows you the candidates, copies your pick into your workspace with copy_gallery_template, and then proceeds with the normal flow (get_design_parameters → generate_pdf_sync). The copy always lands in the workspace you selected on the OAuth consent screen — the AI cannot target any other workspace.

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

Where files are saved (local mode)

Output location is resolved in this order:

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

Build your own agent

The setup above assumes an MCP client that manages its own connection and login. If you are writing the agent yourself — Hugging Face Agents, a custom tool loop, or raw HTTP — the hosted endpoint is open to you directly:

Code

https://mcp.re-port-flow.com/mcp

agents.md — the agent-facing guide: transport details, the ten HTTP tools, the OAuth flow, model selection, and the rules an agent has to follow (never invent business data; copy_gallery_template is not idempotent; passthrough values end up in the PDF's metadata).
examples/ — runnable Python, JavaScript and curl clients, plus a script that walks the OAuth flow and prints an access token.

initialize and tools/list work without credentials, so you can discover the toolset before wiring up authentication. Every tools/call needs a Bearer token.

Hugging Face

Re:port Flow is on the Hub at huggingface.co/reportflow. The Hugging Face SDKs have no MCP OAuth flow of their own, so fetch a token once with examples/oauth/get-token.sh and inject it as an Authorization header — see examples/python/hf_mcp_client.py and examples/javascript/hf-mcp-client.mjs.

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)
`search` / `fetch`	ChatGPT connector convention tools (single string argument), closed-world (`openWorldHint: false`) — they only read your own workspace's internal template catalog, never the web. `search` resolves templates by name; `fetch` returns a template's parameter schema by id. Thin wrappers over `list_templates` / `get_design_parameters` so ChatGPT (incl. Plus/Pro without Developer Mode) can discover and inspect templates.
`search_gallery_templates`	Search the public template gallery (no auth needed) by keyword/category. Returns candidate templates that are not yet in your workspace — their `slug` cannot be used for PDF generation until copied.
`get_gallery_template`	Fetch full details of one public gallery template by `slug` (no auth needed)
`copy_gallery_template`	Write tool. Copy a gallery template into the workspace you authorized (the target workspace is fixed by your access token and cannot be passed as an argument). Returns `designId` + `version` ready for `get_design_parameters` / `generate_pdf_sync`. Each call creates a new design — it never reuses a previous copy.

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 Re:port Flow"
`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

Privacy

Re:port Flow MCP is a thin client: it forwards your requests to your own Re:port Flow account and returns the generated PDFs. It does not sell or share your data with third parties. Authentication tokens are stored locally (OS keychain, or a chmod-0600 file fallback) and are sent only to Re:port Flow's own services — during the OAuth login, and as a Bearer credential on each authenticated API call (listing templates, generating or downloading PDFs). They are never shared with any third party.

For the full privacy policy — what is collected, how long it is retained, and how it is handled — see: lp.re-port-flow.com

Security

The hosted endpoint validates the Host header (DNS-rebinding protection) and rejects structurally invalid Origin headers with 403 Forbidden, per the MCP Streamable HTTP specification's Security requirements. Authentication is Bearer-token only — no cookies, and CORS never allows credentials. The full policy and its threat model are documented in docs/security.md (Japanese).

Support

Need help, found a bug, or have a directory-review question?

Re:port Flow (privacy & support): https://lp.re-port-flow.com
GitHub Issues: https://github.com/re-port-flow/reportflow-mcp/issues

License

MIT — see LICENSE.

Reportflow MCP README