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re-port-flow/reportflow-mcp

re-port-flow/reportflow-mcp

ReportFlow MCP Server - PDF report generation for Claude and AI agents (public publish mirror of monepla/report-mcp)
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add reportflow-mcp -- npx -y reportflow-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
1 ★ · re-port-flow/reportflow-mcp · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 1 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 re-port-flow/reportflow-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

Re:port Flow MCP

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

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:
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.):
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.
Either handshake also returns MCP instructions: a short brief telling the connected AI what Re:port Flow does and how to reach a first PDF (gallery search → copy → parameters → generate), so it can offer to create a document right after you connect instead of waiting to be asked. How closely a client follows those instructions is up to that client.
A2A (Agent2Agent)
The remote server also speaks A2A **v1.0** over the JSON-RPC binding:
- Agent Card: https://mcp.re-port-flow.com/.well-known/agent-card.json
- Endpoint: POST https://mcp.re-port-flow.com/a2a (SendMessage)
Each A2A skill is one of the MCP tools above (the skill id is the tool name). Send a message with a data part {"skill": " ", "arguments": {...}}; the arguments follow that tool's input schema, and the call runs through the same authorization and workspace permissions as MCP. Authorize with the same OAuth flow (the MCP access token works as-is). Streaming, push notifications and task retrieval are not supported: every SendMessage returns a finished task.
来源
awesome · https://github.com/re-port-flow/reportflow-mcp
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