Pandadoc MCP connector for AI agents

Tools your documents agent reaches for on Pandadoc MCP, scoped per user.

CALL ANY TOOL

19 tools covering the full PandaDoc workflow — list, create, update, send, and track documents and templates with per-user OAuth credentials.

pandadocmcp_documents_archive

Archive documents

Archive a document by ID to remove it from active lists without permanently deleting it.

Parameters

Name

Type

Required

Description

document_id

string

Required

Document ID to archive

pandadocmcp_documents_audit_trail_get

Get documents audit trail

pandadocmcp_documents_content_get

Get documents content

pandadocmcp_documents_create

Create documents

pandadocmcp_documents_create_from_markdown

Documents Create From Markdown

pandadocmcp_documents_details_get

Get documents details

pandadocmcp_documents_fields_assign

Documents Fields Assign

pandadocmcp_documents_list

List documents

pandadocmcp_documents_metadata_get

Get documents metadata

pandadocmcp_documents_search

Search documents

pandadocmcp_documents_send

Send documents

pandadocmcp_documents_status_change

Documents Status Change

pandadocmcp_documents_status_get

Get documents status

pandadocmcp_documents_summary_get

Get documents summary

pandadocmcp_documents_update

Update documents

pandadocmcp_templates_create

Create templates

pandadocmcp_templates_details_get

Get templates details

pandadocmcp_templates_list

List templates

Build your Agent

Same auth pattern across every framework.

from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="pandadocmcp")

mcp = MultiServerMCPClient({
    "pandadocmcp": {
        "url": "https://mcp.scalekit.com/pandadocmcp",
        "headers": {"Authorization": "Bearer " + token}
    }
})
tools = await mcp.get_tools()

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "pandadocmcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/pandadocmcp
// Pass: Authorization: Bearer + token

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "pandadocmcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/pandadocmcp
// Pass: Authorization: Bearer + token

from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="pandadocmcp")
# Connect to MCP at https://mcp.scalekit.com/pandadocmcp
# Pass: Authorization: Bearer + token

Try these prompts

Paste any prompt into your agent to get started.

Search & retrieve

Copy the prompt

Copied

List all my draft documents and show their recipients and current status.

Copy the prompt

Copied

Search for all contracts sent in the last 30 days and show their completion status.

Create & send

Copy the prompt

Copied

Create a new NDA from the standard template and send it to john@example.com for signature.

Copy the prompt

Copied

Create a proposal document from markdown, add two recipients, and send it with a custom subject line.

SEE HOW AUTH WORKS

User authorises once. Every agent call after uses their token with scope enforcement.

Authorize

Your user connects

PandaDoc MCP

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

PandaDoc MCP

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

PandaDoc MCP

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

PandaDoc MCP

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other connectors.

SUPPORT

Support ticket automation (Google ADK)

Google ADK agent that classifies Zendesk tickets, pulls Notion context, and posts to Slack. End-to-end ticket handoff.

SUPPORT

Support triage agent

Read Zendesk tickets, fetch runbooks from Notion, and route to the right Slack channel with a drafted response.

GTM

Salesforce customer insights agent

Surface Salesforce account activity, NPS signals, and renewal flags into Slack threads for the account team.

Salesforce

Slack

View agent

Why Scalekit

Secure your agent's access. Connectors ship in minutes

Other connector libraries treat auth as a demo afterthought.

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.

// shared token
 audit → bot_service_account

 // scalekit
 audit → user_abc ✓

02.

Authentication is not authorization

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Pandadoc MCP as the user or as a shared key?

Scalekit resolves a per-user credential for each call. The Pandadoc MCP audit log shows the real user identity, not a shared service account.

Where is the Pandadoc MCP token stored?

In Scalekit's AES-256 encrypted vault, isolated per tenant. Tokens are auto-refreshed before expiry and revocable from a single dashboard without code changes.

Can I limit what the agent is allowed to do in Pandadoc MCP?

Pass a toolNames filter to listScopedTools. Scalekit enforces the allowed set before every API call — the agent cannot invoke tools outside the approved list.

What happens when a user revokes Pandadoc MCP access?

The token is invalidated at the next tool call. The agent fails closed rather than falling back to a shared key. Other users are unaffected and the revocation event is logged with a timestamp.

Can the agent send or sign documents on behalf of a user without their knowledge?

Only if the user has explicitly authorized the agent through Scalekit's OAuth flow. The token Scalekit vaults is scoped to the permissions the user granted. You can further restrict which tools are callable by passing a toolNames filter, so an agent granted read access cannot invoke pandadocmcp_documents_send even if PandaDoc's API would otherwise allow it.

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit