How do I find my Pendo Integration Key?

In Pendo, navigate to **Settings** > **Integrations**. There you can find or generate your Integration Key for API access.

Can I see real-time statistics for my guides?

Yes! Use the `get_pendo_guide_metrics` tool with a Guide ID to retrieve live data on views, clicks, and completion rates.

Does this support looking up individual user metadata?

Absolutely. Use the `get_pendo_visitor` tool to retrieve all identified properties, account association, and activity history for a specific user ID.

Pendo MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Pendo
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Pendo through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "pendo": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Pendo, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Pendo MCP Server

Connect your Pendo subscription to any AI agent and take full control of your product adoption and user engagement workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Pendo through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Guide Management — List all in-app guides and retrieve detailed metadata and performance metrics.
User & Account Insights — Look up detailed profiles for visitors and accounts to understand their journey.
Product Tagging Auditing — List defined pages and features to verify your product instrumentation.
Metadata Schema Discovery — Retrieve schemas for visitor and account metadata to understand available data points.
Segment Overview — List saved user segments to maintain visibility over your audience targeting.

The Pendo MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Pendo to LangChain via MCP

Follow these steps to integrate the Pendo MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Pendo via MCP

Why Use LangChain with the Pendo MCP Server

LangChain provides unique advantages when paired with Pendo through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Pendo MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Pendo queries for multi-turn workflows

Pendo + LangChain Use Cases

Practical scenarios where LangChain combined with the Pendo MCP Server delivers measurable value.

RAG with live data: combine Pendo tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Pendo, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Pendo tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Pendo tool call, measure latency, and optimize your agent's performance

Pendo MCP Tools for LangChain (10)

These 10 tools become available when you connect Pendo to LangChain via MCP:

get_pendo_account

Get details for a specific account

get_pendo_guide

Get details for a specific guide

get_pendo_guide_metrics

Get performance metrics for a guide

get_pendo_visitor

Get details for a specific visitor

list_pendo_applications

List applications tracked in the Pendo subscription

list_pendo_features

List tagged features

list_pendo_guides

) defined in Pendo. List Pendo guides

list_pendo_metadata_schema

List metadata schema definitions

list_pendo_pages

List tagged pages

list_pendo_segments

List saved user segments

Example Prompts for Pendo in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Pendo immediately.

"List all active guides in my Pendo account."

"Get metadata for visitor 'user@example.com'."

"Show me the performance metrics for the guide 'guide_98765'."

Troubleshooting Pendo MCP Server with LangChain

Common issues when connecting Pendo to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Pendo + LangChain FAQ

Common questions about integrating Pendo MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.