PandaDoc MCP

io.github.Servosity由 GitHub 账号 Servosity 发布v0.1.7更新于 Nov 6, 2026

Every PandaDoc endpoint, plus an offline document pipeline no other PandaDoc tool has - stalled

发布方自己的服务:PandaDoc MCP Server

已验证STDIO仅桌面数据与分析商业与电商

概览

AI 生成的概览

非官方的本地 MCP 服务器与 CLI,让助手查询 PandaDoc 文档、报价与收件人,并基于本地 SQLite 镜像做离线汇总。

可以做什么
  • 查询 PandaDoc 的文档、模板、联系人与工作区,覆盖完整 API
  • 生成跨文档汇总:停滞文档、停留时长、未结报价金额、漏斗与预测
  • 查看收件人互动、模板成交率、提醒缺口与冷淡客户
  • 将 PandaDoc 同步到带全文检索的本地 SQLite 镜像,离线回答聚合问题
  • 创建、发送和更新文档、联系人与模板,支持 dry-run 预览
适用场景
适合通过 PandaDoc 发送方案书、SOW 或报价的团队,希望助手直接回答跨文档问题,例如哪些交易停滞、还有多少未结报价金额、今天该跟进谁,而不必导出表格。
运行要求
以本地进程运行,仅限桌面端;通过 .mcpb 安装包或 shell 安装脚本部署 MCP 服务器及其配套 CLI。需要具备 API 访问权限的 PandaDoc 账户和 PANDADOC_API_KEY 凭据;PANDADOC_BASE_URL 默认指向标准主机。多代理安装命令需要 Node.js。
安装前请注意
README 明确警告不要使用 HTTP 模式:该构建没有密码、监听所有网络接口且缺少重绑定防护,应只用 stdio,并关闭任何隧道。工具会用你的凭据修改数据;发送或删除文档、创建 API 密钥或成员令牌等写入操作需人工审核,凭据的权限范围才是真正的限制。项目为非官方、Beta 阶段,与 PandaDoc 公司无关联。

安装

在 SourceWeft 中

  1. 打开 控制台中的 PandaDoc MCP,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

PandaDoc + AI - for Claude, the ChatGPT desktop app, GitHub Copilot, Gemini CLI, and any agent that speaks MCP

Unofficial. Community-built Claude Code Skill and MCP server for the PandaDoc API. Not affiliated with, endorsed by, or sponsored by PandaDoc, Inc..

[PandaDoc demo - animated preview]

▶ Watch the 30-second demo - demo data is simulated; every command shown exists in the real CLI.

Every PandaDoc endpoint, plus an offline document pipeline no other PandaDoc tool has - stalled deals, aging, recipient engagement, and open quote value from a local store. Works with the AI you already use - ChatGPT (desktop app), Claude Desktop, Codex, Claude Code, Claude Cowork, and GitHub Copilot - plus Gemini CLI. Free, open source, runs on your laptop. Built for MSP owners. No code required.

Works with your agent

Security note (until this connector is reprinted). Do not run HTTP mode (--transport http), not even on localhost. This build has no password, listens on every network interface, and predates the browser-rebinding guard, so a web page you open can reach it. The MCP tools can also make changes with your credentials. Use the default stdio transport. If you set up a tunnel for a remote agent, shut it down. A fix is on the way.

The six agents MSP owners actually use (self-serve, works today):

Your AI agentHow to install the PandaDoc skill
Claude DesktopRun installer, then Settings > Extensions to register pandadoc-mcp (no JSON editing).
ChatGPT (desktop app)Run installer, then add pandadoc-mcp in Settings > MCP servers as a local (STDIO) server. ChatGPT on the web is not supported yet.
Codex CLIPaste the install prompt below.
Claude CodePaste the install prompt below.
Claude CoworkPaste the install prompt below.
GitHub Copilot (VS Code)Run installer, add pandadoc-mcp to mcp.json under the servers key, then pick Agent mode.

The ChatGPT desktop app runs pandadoc-mcp locally and shares MCP configuration with Codex (OpenAI). ChatGPT on the web needs a remote (HTTP) server, and this connector's HTTP mode is paused until it is reprinted (see the security note in mcp-install.md), so msp-skills does not support it yet. If your team works there, a hosted gateway is the better pick; check that your AI app is on the gateway's setup list.

Also for the Microsoft and Google stacks

Big install base, but an honest heads-up: Gemini CLI runs the local binary you just installed, while Microsoft 365 Copilot and the Gemini app need a remote server, which msp-skills does not support yet.

AgentWhat it takes
Microsoft 365 Copilot / Copilot StudioNot supported by msp-skills yet: it needs a remote server. A hosted gateway is the better pick; check that your AI app is on the gateway's setup list.
Google GeminiGemini CLI is local - same as Claude Code. See mcp-install.md. The Gemini app needs a remote server and is not supported by msp-skills yet.

Skill-native agents (also covered): Hermes and OpenClaw read this skill's SKILL.md directly and speak MCP - see their install sections below. Also works with Cursor, Windsurf, Cline, Continue.dev, and Zed via MCP. Full per-tool wire-up: docs/which-agent.md.

Run more than one agent? Install across all 51+ supported agents in one command: npx skills add Servosity/msp-skills@latest (requires Node.js, then run the per-skill installer for the CLI/MCP binaries). See docs/which-agent.md.

Install in 60 seconds

Fastest for Claude Desktop - one-click .mcpb

Claude Desktop bundle: the .mcpb launches on macOS (Intel and Apple Silicon), Windows x64 and Linux x64. Every tool shells out to the companion pandadoc-cli. Releases cut from 2026-09-18 on ship that CLI inside the bundle; older bundles contain only the MCP server, so if yours lacks the companion, run the Path A or Path B installer below first (or set PANDADOC_CLI_PATH to an existing binary). Details: #331.

Download PandaDoc MCP (.mcpb) - then open Claude Desktop > Settings > Extensions and select the file. One click, no JSON, no shell. (Browse every PandaDoc release on the releases page.)

Prefer the Claude Code plugin? Add the marketplace once, then install - works immediately, no directory listing required:

/plugin marketplace add Servosity/msp-skills/plugin install pandadoc@msp-skills

Path A - paste one prompt into your AI agent (recommended)

Copy this into Claude Code, Codex CLI, or Claude Cowork:

Install the PandaDoc Skill and MCP server from Servosity/msp-skills in this agent workspace. If this workspace uses a POSIX shell (macOS, Linux, WSL, or Bash), run bash <(curl -fsSL https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/pandadoc/install.sh). If it uses Windows PowerShell, run iwr -useb https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/pandadoc/install.ps1 | iex. Then authenticate per the README and run pandadoc-cli --help to explore.

The same prompt works in any agent that can run shell.

Path B - run the installer yourself

Windows (PowerShell):

powershell
iwr -useb https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/pandadoc/install.ps1 | iex

macOS / Linux:

bash
bash <(curl -fsSL https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/pandadoc/install.sh)

The installer drops both pandadoc-cli (the CLI) and pandadoc-mcp (the MCP server) into your user bin path. Claude Code, Codex, and Cowork discover the Skill via SKILL.md in this directory.

Verify:

bash
pandadoc-cli --version

Upgrade to the latest version

The installer always fetches the current release - re-run it to upgrade:

macOS / Linux:

bash
bash <(curl -fsSL https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/pandadoc/install.sh)

Windows (PowerShell):

powershell
iwr -useb https://raw.githubusercontent.com/Servosity/msp-skills/main/skills/pandadoc/install.ps1 | iex

Claude Desktop .mcpb users: download the latest .mcpb (top of this section) and re-select it in Settings > Extensions. Claude Code plugin users: /plugin update pandadoc@msp-skills.

Add to Claude Desktop, the ChatGPT desktop app, GitHub Copilot, Gemini CLI, or another MCP client

After the installer runs, see mcp-install.md and docs/which-agent.md for the per-agent wire-up - one section per agent, including the GitHub Copilot servers key and the ChatGPT desktop app. Claude Desktop's Settings > Extensions panel is the simplest path; the MCP config block (for users who prefer editing JSON) is documented in mcp-install.md.

Install for Hermes

From the Hermes CLI:

bash
hermes skills install servosity/msp-skills/skills/pandadoc --force

Inside a Hermes chat session:

/skills install servosity/msp-skills/skills/pandadoc --force

Hermes speaks MCP natively, so it can also use the pandadoc-mcp server directly - same install path, same env vars.

Install for OpenClaw

Tell your OpenClaw agent (copy this):

Install the pandadoc skill from https://github.com/servosity/msp-skills/tree/main/skills/pandadoc. The skill defines how its required CLI (pandadoc-cli) can be installed via the openclaw: frontmatter block.

OpenClaw isn't generally available yet; the frontmatter wiring is pre-shipped and will activate the moment OpenClaw launches.

Authenticate

Set the credentials the CLI needs (from your PandaDoc portal):

bash
PANDADOC_API_KEY=<value> pandadoc-cli doctor

doctor confirms the credentials work before you run anything that touches data. It exits 0 even when the credential is rejected, so scripts should add --fail-on error.

What this skill does

Question your MSP keeps askingCommand
Which documents were sent but never completed?pandadoc-cli stalled --days 14
How much money is tied up in open quotes?pandadoc-cli value
What does my whole document funnel look like?pandadoc-cli pipeline
How long has each document sat in its current status?pandadoc-cli aging
Which clients haven't signed anything in a month?pandadoc-cli cold-clients --days 30
Who should I follow up with today?pandadoc-cli followup --days 7
Which recipients open and sign vs. let documents sit?pandadoc-cli engagement
Which templates actually close?pandadoc-cli template-stats
Which sent documents have no auto-reminder set?pandadoc-cli reminder-gaps
What changed in the last day?pandadoc-cli since 24h

Full command reference: guide.md. For the AI-agent operating contract (--agent, --dry-run, when to confirm before mutating), see AGENTS.md.

What makes this different

Most PandaDoc integrations and MCP servers proxy each question into a live API call. That's fine for one record. It dies at scale, when you're asking "across every open document, how much is unsigned and how old is it?" at QBR time.

This skill syncs PandaDoc into a local SQLite mirror with full-text search. Aggregate questions become one local SQL join: instant, offline, and the AI sees the answer, not the raw data. Compound commands like followup, forecast, and cold-clients join across documents, recipients, and quote pricing - work a stateless API wrapper can't do.

The pain this closes

You send proposals, SOWs, and MSAs through PandaDoc and then they go quiet. The deal isn't dead - it's just sitting, unsigned, and nothing tells you. On r/msp the recurring thread is some version of "how do you follow up on quotes that never get signed?" - owners trade reminder cadences precisely because the proposal tool surfaces one document at a time and never says this deal stalled or you have this much in quotes nobody has touched in three weeks. So follow-up depends on memory and the forecast is a guess.

  • pandadoc-cli stalled --days 14 - sent but never completed: the deals quietly dying.
  • pandadoc-cli value - total open quote dollars across every in-flight document.
  • pandadoc-cli followup --days 7 - a ranked nudge worklist joined to recipient emails.
  • pandadoc-cli cold-clients --days 30 - accounts that have gone quiet, ranked by days since last signature.
  • pandadoc-cli forecast - open quote dollars bucketed into healthy, aging, and stalled tiers.

See pain-point.md for the longer narrative.

Frequently asked questions

Does this work with ChatGPT?

Yes, in the ChatGPT desktop app. It runs MCP servers locally (STDIO), the way pandadoc-mcp runs, and shares MCP configuration with Codex (OpenAI): add pandadoc-mcp under Settings > MCP servers as a STDIO server, or add it once to Codex's ~/.codex/config.toml. ChatGPT on the web is not supported by msp-skills yet: it needs a remote (HTTP) server, and this connector's HTTP mode is paused until it is reprinted; the security note in mcp-install.md explains why. If your team works there, a hosted gateway is the better pick; check that your AI app is on the gateway's setup list.

Does this work with Codex, Cursor, Windsurf, Cline, Copilot, or Gemini?

Yes - all of them speak MCP. Cross-tool install commands are in the matrix above and the deep-dive in docs/which-agent.md.

Do I need to know how to code?

No. The recommended install is to paste one sentence into Claude Code or Codex - your agent reads SKILL.md and does the install. The fallback is a one-line installer per OS (bash or PowerShell). Neither path requires writing code. You'll enter your PandaDoc credentials once.

Is my PandaDoc data safe?

Your data stays on your machine. The CLI and MCP server are local binaries. The SQLite mirror sits in a directory under your user account. The AI agent only sees what the CLI returns - typically a query result, not raw bulk data. Credentials are read from your environment or your agent's config; never bundled into this repo or transmitted anywhere by MSP Skills.

Will this hit my PandaDoc API rate limits?

Day-to-day questions read the local mirror, so they never touch the API. Only sync, tail, and a few live commands (such as reminder-gaps) call PandaDoc directly, and the CLI honors a configurable --rate-limit so you stay inside your plan's limits.

Do I need to be a PandaDoc partner or customer?

You need your own PandaDoc account with API access (included on PandaDoc's paid plans). The skill authenticates with your own PANDADOC_API_KEY - there is no Servosity or PandaDoc partner requirement.

Will this replace my PandaDoc portal?

No. You still create, send, and sign documents in PandaDoc. This adds the cross-document reporting and follow-up rollups the portal doesn't surface, so you can ask your AI instead of exporting spreadsheets.

What does it cost?

Free. Apache-2.0 licensed. You pay only for whichever AI agent you use (Claude, ChatGPT, Codex, etc.), and that's billed by your AI provider, not by us.

Safety model

TierExamplesRecommended agent policy
Readpipeline, stalled, aging, value, engagement, search, documents listAllow
Write (routine)contacts create, contacts update, documents create, documents send document, documents recipients add-document, templates createPreview with --dry-run, then a reviewed write
Credential / destructiveworkspaces api-keys create, members token create-member, documents delete, documents bulk-delete, documents recipients delete-documentHuman-in-the-loop only

The strongest control is the scope you grant the PandaDoc credentials - the CLI can only do what the credentials are permitted to do. Full details, including how to lock it down, are in governance.md.

Status

Beta. Validated against the PandaDoc API surface and being validated with MSPs running it live against their own production tenant in our weekly Build Sessions. RSVP at compoundingteams.com/build-sessions.


Standards. Conforms to the open Agent Skills spec (Anthropic, Dec 2025; 40+ agents). MCP-compatible - works with any MCP-capable agent including Hermes. OpenClaw-ready (frontmatter pre-wired, awaiting OpenClaw launch).

Maintained by Servosity. Apache-2.0 licensed. Built with CLI Printing Press. Last updated: 2026-06-06.

来源:skills/pandadoc/README.md,提交 061ec05

工具

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SourceWeft 曾在隔离沙箱中以无凭据方式启动该软件包一次,以列出其工具,但未能完成:该软件包类型无法在沙箱中运行。

版本历史

5
  1. v0.1.7最新Oct 23, 2026
  2. v0.1.6Oct 23, 2026
  3. v0.1.5Oct 22, 2026
  4. v0.1.4Oct 16, 2026
  5. v0.1.3Sep 16, 2026

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其他 Pandadoc 集成