How to integrate Zep MCP with LangChain

This guide walks you through connecting Zep to LangChain using the Composio tool router. By the end, you'll have a working Zep agent that can store a memory about today's meeting, retrieve all memories tagged urgent, summarize knowledge about client preferences through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Zep account through Composio's Zep MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide will help you understand how to give your LangChain agent real control over a Zep account through Composio's Zep MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Zep with

ChatGPT OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenCode Cursor VS Code OpenClaw Hermes CLI Google ADK Vercel AI SDK Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

Get and set up your OpenAI and Composio API keys
Connect your Zep project to Composio
Create a Tool Router MCP session for Zep
Initialize an MCP client and retrieve Zep tools
Build a LangChain agent that can interact with Zep
Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

Agent Framework: Build agents that can use tools and make decisions
MCP Integration: Connect to external services through Model Context Protocol adapters
Memory Management: Maintain conversation history across interactions
Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Zep MCP server, and what's possible with it?

The Zep MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zep account. It provides structured and secure access so your agent can perform Zep operations on your behalf.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS

Prerequisites

Before starting this tutorial, make sure you have:

Python 3.10 or higher installed on your system
A Composio account with an API key
An OpenAI API key
Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
Keep the API key safe.

Composio API Key

Log in to the Composio dashboard.
Navigate to your API settings and generate a new API key.
Store this key securely as you'll need it for authentication.

Install dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

@composio/langchain provides Composio integration for LangChain
@langchain/mcp-adapters enables MCP client connections
@langchain/core is the core agent framework
dotenv/config loads environment variables

Set up environment variables

bash

COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

COMPOSIO_API_KEY authenticates your requests to Composio's API
COMPOSIO_USER_ID identifies the user for session management
OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();

What's happening:

We're importing LangChain's MCP adapter and Composio SDK
The dotenv/config import loads environment variables from your .env file
This setup prepares the foundation for connecting LangChain with Zep functionality through MCP

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

What's happening:

We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
Creating a Composio instance that will manage our connection to Zep tools
Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['zep']
    }
);

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Zep tools
The create method takes the user ID and specifies which toolkits should be available
The returned session.mcp.url is the MCP server URL that your agent will use
This approach allows the agent to dynamically load and use Zep tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "zep-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });

What's happening:

We're creating a MultiServerMCPClient that connects to our Zep MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Zep tools that the agent can use
We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Zep related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });

What's happening:

We initialize an empty conversationHistory list to maintain context across interactions
A readline interface is used to continuously accept user input from the command line
When a user types a message, it's added to the conversation history and sent to the agent
The agent processes the request using the invoke() method with the full conversation history
Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

What's happening:

We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Zep and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['zep']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "zep-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Zep related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Zep through Composio's Tool Router.

Key features of this implementation:

Dynamic tool loading through Composio's Tool Router
Conversation history maintenance for context-aware responses
Async Python provides clean, efficient execution of agent workflows

You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

TOOLS

Supported Tools

Every Zep action and event your agent gets out of the box.

Add Fact Triple

Tool to add a manually specified fact triple (subject-predicate-object) to the Zep knowledge graph.

Add Session Memory

Tool to add memory messages to a specified Zep session.

Add Thread Messages

Tool to add chat messages to a thread in Zep and ingest them into the user knowledge graph.

Clone Graph

Tool to clone a user or group graph with new identifiers in Zep.

Create Graph

Tool to create a new graph by adding data to Zep.

Create Group

Tool to create a new group in Zep for multi-user graph management.

Create Session

Tool to create a new session in Zep for storing conversation memory.

Create Thread

Tool to create a new thread in Zep for a specific user.

Create User

Tool to create a new user in Zep with properties like user_id, email, and metadata.

Delete Graph

Tool to delete a graph from Zep.

Delete Group

Tool to delete a group from Zep.

Delete Session Memory

Tool to delete a session and its memory from Zep.

Delete Thread

Tool to delete a thread and its messages from Zep.

Delete User

Tool to delete a user and all associated threads and artifacts from Zep.

Get Edge by UUID

Tool to retrieve a specific edge by its UUID from the Zep knowledge graph.

Get Graph by ID

Tool to retrieve a graph by its unique identifier from Zep.

Get Group by ID

Tool to retrieve a group by ID from Zep.

Get Node Entity Edges

Tool to retrieve all entity edges for a specific node in the Zep knowledge graph.

Get Project Info

Tool to retrieve project information based on the provided API key.

Get Session by ID

Tool to retrieve a session by its unique identifier from Zep.

Get Session Memory

Tool to retrieve memory for a given session including relevant facts and entities.

Get Session Message by UUID

Tool to retrieve a specific message by UUID from a Zep session.

Get Session Messages

Tool to retrieve messages for a given session from Zep.

Get Task Status

Tool to check the status of asynchronous operations in Zep.

Get Thread Messages

Tool to retrieve conversation history for a specific thread from Zep.

Get Thread User Context

Tool to retrieve the most relevant user context from the user graph based on thread messages.

Get User by ID

Tool to retrieve a user by their user ID from Zep.

Get User Node

Tool to retrieve a user's graph node and summary from Zep.

Get User Nodes

Tool to retrieve all nodes for a specific user from their graph in Zep.

Get User Sessions

Tool to retrieve all sessions for a user from Zep.

Get User Threads

Tool to retrieve all threads for a specific user from Zep.

Graph Search

Tool to perform hybrid graph search combining semantic similarity and BM25 full-text search across the Zep knowledge graph.

List Graphs

Tool to retrieve all graphs from Zep with pagination support.

List Groups Ordered

Tool to retrieve all groups from Zep with pagination support.

List Sessions Ordered

Tool to retrieve all sessions from Zep with pagination and ordering support.

List Threads

Tool to retrieve all threads from Zep with pagination support.

List Users Ordered

Tool to retrieve all users from Zep with pagination support.

List All Threads

Tool to list all threads with pagination and ordering support.

Update Graph

Tool to update graph information in Zep including name and description.

Update Group

Tool to update group information in Zep including name, description, and fact rating instructions.

Update Message

Tool to update a message in a Zep thread.

Update Session Metadata

Tool to update session metadata in Zep.

Update User

Tool to update an existing user's information in Zep including email, metadata, and ontology settings.

FRAMEWORKS

How to build Zep MCP Agent with another framework

ChatGPT

Use Zep MCP with ChatGPT

OpenAI Agents SDK

Use Zep MCP with OpenAI Agents SDK

Claude Agent SDK

Use Zep MCP with Claude Agent SDK

Claude Code

Use Zep MCP with Claude Code

Claude Cowork

Use Zep MCP with Claude Cowork

Codex

Use Zep MCP with Codex

Cursor

Use Zep MCP with Cursor

OpenClaw

Use Zep MCP with OpenClaw

Hermes

Use Zep MCP with Hermes

CLI

Use Zep MCP with CLI

Google ADK

Use Zep MCP with Google ADK

Vercel AI SDK

Use Zep MCP with Vercel AI SDK

Mastra AI

Use Zep MCP with Mastra AI

LlamaIndex

Use Zep MCP with LlamaIndex

CrewAI

Use Zep MCP with CrewAI

OpenCode

Use Zep MCP with OpenCode

VS Code

Use Zep MCP with VS Code

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Google Sheets

Oauth2

Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.

Composio

No Auth

Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed.

Notion

Oauth2Api Key

Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.

Airtable

Oauth2Api Key

Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.

FAQ

Frequently asked questions

With a standalone Zep MCP server, the agents and LLMs can only access a fixed set of Zep tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zep and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Zep tools.

Yes, absolutely. You can configure which Zep scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Zep data and credentials are handled as safely as possible.

Start with Zep.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Zep tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Zep MCP with LangChain

Connect Zep without auth hassles

Introduction

Also integrate Zep with

TL;DR

What is LangChain?

What is the Zep MCP server, and what's possible with it?

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Initialize Composio client

Create a Tool Router session

Configure the agent with the MCP URL

Set up interactive chat interface

Run the application

Complete Code

Conclusion

Supported Tools

How to build Zep MCP Agent with another framework

ChatGPT

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

Cursor

OpenClaw

Hermes

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

OpenCode

VS Code

Explore Other Toolkits

Google Sheets

Composio

Notion

Airtable

Frequently asked questions

What are the differences in Tool Router MCP and Zep MCP?+

Can I use Tool Router MCP with LangChain?+

Can I manage the permissions and scopes for Zep while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Zep.It takes 30 seconds.

Teams ship real agents on Composio