PandaDoc MCP

PandaDoc + AI - for ChatGPT, Claude, GitHub Copilot, Microsoft 365 Copilot, Gemini, 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..

_{▶ 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 (Plus/Pro+), Claude Desktop, Codex, Claude Code, Claude Cowork, and GitHub Copilot - plus Microsoft 365 Copilot / Copilot Studio and Google Gemini via the remote path. Free, open source, runs on your laptop. Built for MSP owners. No code required.

Works with your agent

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

Your AI agent	How to install the PandaDoc skill
Claude Desktop	Run installer, then Settings > Extensions to register pandadoc-mcp (no JSON editing).
ChatGPT (paid plans)	Run installer, expose pandadoc-mcp over HTTPS, register as a Developer Mode connector.
Codex CLI	Paste the install prompt below.
Claude Code	Paste the install prompt below.
Claude Cowork	Paste the install prompt below.
GitHub Copilot (VS Code)	Run installer, add pandadoc-mcp to mcp.json under the servers key, then pick Agent mode.

For ChatGPT, run pandadoc-mcp --transport http and expose that behind HTTPS - no bridge package is needed. See mcp-install.md.

Also for the Microsoft and Google stacks

Big install base, but an honest heads-up: these are the remote / enterprise path, not the local binary you just installed.

Agent	What it takes
Microsoft 365 Copilot / Copilot Studio	Not self-serve. Host pandadoc-mcp over HTTPS, then wire it into Copilot Studio (Tools > Add a tool > Model Context Protocol > Server URL) or a declarative agent. Needs a Copilot Studio license + tenant admin. See mcp-install.md.
Google Gemini	Gemini CLI is local - same as Claude Code. The Gemini app is remote - same HTTPS path as ChatGPT. See mcp-install.md.

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):

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

macOS / Linux:

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:

pandadoc-cli --version

Upgrade to the latest version

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

macOS / Linux:

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

Windows (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, GitHub Copilot, Gemini CLI, Microsoft 365 Copilot, 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 remote Microsoft 365 Copilot / Copilot Studio path. 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:

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):

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 asking	Command
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, on Plus, Pro, Team, Business, Enterprise, and Education plans (Free tier does not yet expose Developer Mode). ChatGPT connects to remote MCP servers over HTTPS, not local stdio binaries. The PandaDoc MCP server runs locally, but it speaks HTTP natively: start it with pandadoc-mcp --transport http --addr :7777 and put it behind an HTTPS tunnel or your own reverse proxy. No bridge package is involved. Step-by-step in mcp-install.md.

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

Tier	Examples	Recommended agent policy
Read	pipeline, stalled, aging, value, engagement, search, documents list	Allow
Write (routine)	contacts create, contacts update, documents create, documents send document, documents recipients add-document, templates create	Preview with --dry-run, then a reviewed write
Credential / destructive	workspaces api-keys create, members token create-member, documents delete, documents bulk-delete, documents recipients delete-document	Human-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.

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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.