Re:port Flow MCP

MCP serverDocs & knowledge

ReportFlow lets your AI create polished PDF reports from your Re:port Flow templates. Once added, you can ask your AI to turn data or notes into a finished, shareable document without building it yourself.

Use Re:port Flow MCP in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Re:port Flow MCP and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use Re:port Flow MCP to search gallery templates

Details

Available today. Use it from your connected AI after setup.

Add ReportFlow, then ask your AI to create a PDF report from one of your Re:port Flow templates.

Re:port Flow MCPStart free

What your AI can do with it

  • Generate PDF reports from your Re:port Flow templates
  • Turn notes or data into a finished, shareable document
  • Produce reports on request without leaving the conversation

Install Re:port Flow MCP

The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.

  • Claude Code

    claude mcp add --transport http --scope user re-port-flow-mcp 'https://mcp.re-port-flow.com/mcp'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

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

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=re-port-flow-mcp&config=eyJ1cmwiOiJodHRwczovL21jcC5yZS1wb3J0LWZsb3cuY29tL21jcCJ9

    Open the link and Cursor adds the server at that address.

  • ChatGPT

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

    In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.

  • Codex

    codex mcp add re-port-flow-mcp --url 'https://mcp.re-port-flow.com/mcp'

    Run it once, then sign in with codex mcp login re-port-flow-mcp if the server asks for an account.

From the project's README

As published by re-port-flow/reportflow-mcp in README.md.

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:

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.):

{
  "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

CommandPurpose
/generate_pdfStep-by-step recipe for a single PDF
/generate_pdfsRecipe for batch PDF generation
/reportflow_helpQuick feature tour

Where files are saved (local mode)

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

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:

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)

ToolPurpose
authenticateFirst-time / re-authentication
list_templatesList available designs
get_design_parametersFetch the parameter schema for a design
generate_pdf_sync / _asyncGenerate one PDF (sync returns path; async returns request ID)
generate_pdfs_sync / _asyncGenerate many PDFs (returns a ZIP)
download_file / download_zipDownload artifacts produced by async tools
suggest_paramsTranslate a natural-language brief into a params JSON via MCP Sampling (requires a Sampling-capable client)
search / fetchChatGPT 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_templatesSearch 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_templateFetch full details of one public gallery template by slug (no auth needed)
copy_gallery_templateWrite 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)

URIContents
reportflow://designsList of available designs
reportflow://designs/{designId}/parametersParameter schema for one design
reportflow://errorsCatalog of error messages from the Content Service
reportflow://server-infoServer feature overview

Prompts (slash-command recipe cards)

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

Troubleshooting

SymptomFix
Error containing re-authentication requiredAsk the AI: "re-authenticate with Re:port Flow"
npx cannot find the packagenpm cache clean --force then retry
No keychain available on LinuxFalls back automatically to a chmod-0600 file under $XDG_STATE_HOME/reportflow-mcp/
Browser cannot open over SSH / remote shellAuthenticate 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?

License

MIT — see LICENSE.

Links

Tools it offers (2)

What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.

  • search_gallery_templates
  • get_gallery_template

Signals

GitHub stars
1
Forks
1
Last commit
Sep 2026
Weekly downloads
68
Advanced
Delivery
reportflow-mcp MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
io-github-re-port-flow-reportflow-mcp
Source
github.com/re-port-flow/reportflow-mcp
Hosted endpoint
https://mcp.re-port-flow.com/mcp