How to integrate Fibery MCP with LangChain

This guide walks you through connecting Fibery to LangChain using the Composio tool router. By the end, you'll have a working Fibery agent that can list all open tasks for your team, fetch details for project entity by id, delete file attachment from a task through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Fibery account through Composio's Fibery MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Fibery

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Fibery is a collaborative work management platform for organizing projects, documents, and knowledge. It helps teams streamline workflows and centralize information in one space.

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Introduction

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

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

Also integrate Fibery with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex 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 Fibery project to Composio
Create a Tool Router MCP session for Fibery
Initialize an MCP client and retrieve Fibery tools
Build a LangChain agent that can interact with Fibery
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 Fibery MCP server, and what's possible with it?

The Fibery MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fibery account. It provides structured and secure access to your workspace data, so your agent can perform actions like querying entities, managing custom apps, running GraphQL queries, and organizing files—all with zero manual integration code.

Entity query and retrieval: Instantly fetch detailed information or lists of entities based on type, filters, and fields, making it easy to surface project or task data as needed.
Custom app and endpoint management: Let your agent list, inspect, or delete custom apps and endpoints, streamlining workspace configuration and app lifecycle management.
Flexible data manipulation with GraphQL: Execute custom GraphQL queries and mutations against your Fibery space to fetch, update, or manipulate structured data programmatically.
File and resource cleanup: Remove outdated files or entities efficiently, helping keep your workspace organized and clutter-free with automated deletions.
Authentication and workspace insights: Validate tokens securely and retrieve workspace or app metadata, ensuring your agent always operates with up-to-date context and permissions.

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 Fibery 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 Fibery 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: ['fibery']
    }
);

const url = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Fibery 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 Fibery tools as needed

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "fibery-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 Fibery MCP server via HTTP
The client is configured with a name and the URL from our Tool Router session
getTools() retrieves all available Fibery 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 Fibery 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 Fibery 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: ['fibery']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "fibery-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 Fibery 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 Fibery 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 Fibery action and event your agent gets out of the box.

Delete Custom App Endpoint

Tool to delete a specific custom app endpoint.

Delete Entity

Permanently delete a Fibery entity by its UUID and type.

Delete File

Delete a file from Fibery storage using its secret identifier.

Execute GraphQL Query

Execute GraphQL queries or mutations against a Fibery workspace.

Get App Information

Tool to retrieve application information.

Get Custom App Endpoints

Tool to list custom app endpoints.

Get Custom Apps

Tool to list all custom apps in the Fibery workspace.

Get File

Download a file from Fibery by its secret or ID.

Get GraphQL Schema

Retrieves the GraphQL schema for the Fibery workspace using standard GraphQL introspection.

Get User Preferences

Tool to retrieve the current user's UI preferences.

Refresh access token

Tool to validate and refresh an access token.

Validate Fibery authentication and get access token

Validates Fibery API authentication and returns the active access token.

Create Entity

Tool to create a new Fibery entity.

Count Entities by Type

Count the total number of entities for a given Fibery type (database).

Fetch Datalist Options

Fetches one page of distinct values for a specific field from a Fibery entity type.

Fetch Schema

Fetch the complete schema metadata for a Fibery workspace.

Exchange OAuth2 authorization code

Exchange an OAuth2 authorization code for access and refresh tokens.

Delete/Revoke Access Token

Delete/revoke an existing Fibery API access token by its ID.

Validate Fibery Workspace Credentials

Validates Fibery workspace credentials by performing a test API query to retrieve the authenticated user's name.

Validate Filter

Validates filter definitions before executing data queries.

Update Entity

Update an existing Fibery entity's fields.

Update User Preferences

Tool to update the current user's preferences by using the Commands API.

Upload File

Upload a file to Fibery's file storage.

FRAMEWORKS

How to build Fibery MCP Agent with another framework

OpenAI Agents SDK

Use Fibery MCP with OpenAI Agents SDK

Claude Agent SDK

Use Fibery MCP with Claude Agent SDK

Claude Code

Use Fibery MCP with Claude Code

Claude Cowork

Use Fibery MCP with Claude Cowork

Codex

Use Fibery MCP with Codex

OpenClaw

Use Fibery MCP with OpenClaw

Hermes

Use Fibery MCP with Hermes

CLI

Use Fibery MCP with CLI

Google ADK

Use Fibery MCP with Google ADK

Vercel AI SDK

Use Fibery MCP with Vercel AI SDK

Mastra AI

Use Fibery MCP with Mastra AI

LlamaIndex

Use Fibery MCP with LlamaIndex

CrewAI

Use Fibery MCP with CrewAI

MORE TOOLKITS

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Google Sheets

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Notion

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Airtable

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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.

Asana

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Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.

FAQ

Frequently asked questions

With a standalone Fibery MCP server, the agents and LLMs can only access a fixed set of Fibery tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Fibery 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 Fibery tools.

Yes, absolutely. You can configure which Fibery 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 Fibery data and credentials are handled as safely as possible.

Start with Fibery.It takes 30 seconds.

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

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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 Fibery MCP with LangChain

Connect Fibery without auth hassles

Introduction

Also integrate Fibery with

TL;DR

What is LangChain?

What is the Fibery 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 Fibery MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Google Sheets

Notion

Airtable

Asana

Frequently asked questions

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

Can I use Tool Router MCP with LangChain?+

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

How safe is my data with Composio Tool Router?+

Start with Fibery.It takes 30 seconds.

Teams ship real agents on Composio