# How to integrate Givebutter MCP with LangChain

```json
{
  "title": "How to integrate Givebutter MCP with LangChain",
  "toolkit": "Givebutter",
  "toolkit_slug": "givebutter",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/givebutter/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/givebutter/framework/langchain.md",
  "updated_at": "2026-05-06T08:13:30.553Z"
}
```

## Introduction

This guide walks you through connecting Givebutter to LangChain using the Composio tool router. By the end, you'll have a working Givebutter agent that can create a new fundraising campaign for our school, list all recent payouts to our nonprofit account, get details for fund with id fund_abc123 through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Givebutter account through Composio's Givebutter MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Givebutter with

- [OpenAI Agents SDK](https://composio.dev/toolkits/givebutter/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/givebutter/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/givebutter/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/givebutter/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/givebutter/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/givebutter/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/givebutter/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/givebutter/framework/cli)
- [Google ADK](https://composio.dev/toolkits/givebutter/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/givebutter/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/givebutter/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/givebutter/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/givebutter/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Givebutter project to Composio
- Create a Tool Router MCP session for Givebutter
- Initialize an MCP client and retrieve Givebutter tools
- Build a LangChain agent that can interact with Givebutter
- 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 Givebutter MCP server, and what's possible with it?

The Givebutter MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Givebutter account. It provides structured and secure access to your fundraising platform, so your agent can perform actions like creating campaigns, tracking donations, managing contacts, and handling payouts on your behalf.
- Campaign management and creation: Easily instruct your agent to start new fundraising campaigns, update campaign details, or remove old campaigns when needed.
- Donation and payout tracking: Ask your agent to retrieve lists of payouts, monitor donation flows, and keep tabs on your fundraising progress in real time.
- Contact and member administration: Let your agent add, archive, or delete contacts, and fetch lists of campaign members for smooth supporter management.
- Fund and webhook operations: Direct your agent to get details about specific funds, create or remove webhooks for event notifications, and manage fundraising infrastructure automatically.
- Automated data cleanup: Empower your agent to archive or delete obsolete contacts, funds, or webhooks, keeping your Givebutter account organized and up to date.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GIVEBUTTER_ARCHIVE_CONTACT` | Archive Contact | Tool to archive a contact by their id. use after ensuring the contact has no associated data (e.g., no transactions or communications). example: "archive contact abc123". |
| `GIVEBUTTER_CREATE_CAMPAIGN` | Create Campaign | Tool to create a new campaign. use when you have title, description, goal, and type ready, after confirming your givebutter account is authenticated. |
| `GIVEBUTTER_CREATE_WEBHOOK` | Create Webhook | Tool to create a new webhook subscription. use when you need to receive real-time notifications programmatically after confirming your endpoint can validate givebutter's signing secret. |
| `GIVEBUTTER_DELETE_CAMPAIGN` | Delete Campaign | Tool to delete a campaign by its id. use after confirming the campaign has no funds raised. example: "delete campaign abc123". |
| `GIVEBUTTER_DELETE_CONTACT` | Delete Contact | Tool to delete a contact by their id. use after confirming the contact has no associated data (e.g., no transactions or communications). example: "delete contact abc123". |
| `GIVEBUTTER_DELETE_FUND` | Delete Fund | Tool to delete a fund by its id. use when you need to remove a fund after confirming it exists. example: "delete fund fund abc123". |
| `GIVEBUTTER_DELETE_WEBHOOK` | Delete Webhook | Tool to delete a webhook by its id. use when you need to remove an obsolete webhook after confirming no further events are needed. example: "delete webhook abc123". |
| `GIVEBUTTER_GET_FUND` | Get Fund | Tool to retrieve details of a specific fund by its id. use after confirming the fund id is valid. |
| `GIVEBUTTER_GET_MEMBERS` | Get Members | Tool to retrieve a paginated list of members for a given campaign. use when you need to list or process campaign members. |
| `GIVEBUTTER_GET_PAYOUTS` | Get Payouts | Tool to retrieve a list of payouts associated with your account. use when you need to list withdrawal transactions after authentication. |
| `GIVEBUTTER_GET_PLANS` | Get Plans | Tool to retrieve a list of plans associated with your account. use after authentication to fetch recurring donation plans. |
| `GIVEBUTTER_GET_TEAMS` | Get Teams | Tool to retrieve a list of teams for a specific campaign. use after creating or updating a campaign when you need to list fundraising teams. example: "get teams for campaign camp123". |
| `GIVEBUTTER_GET_TICKETS` | Get Tickets | Tool to retrieve a list of tickets. use when you need to list all tickets for your account after authentication. |
| `GIVEBUTTER_GET_TRANSACTIONS` | Get Transactions | Tool to retrieve a list of transactions associated with your account. use when you need to list all donations and payments, optionally filtered by scope. |
| `GIVEBUTTER_GET_WEBHOOKS` | Get Webhooks | Tool to retrieve all webhooks configured for your account. use after obtaining valid authentication. |
| `GIVEBUTTER_UPDATE_CAMPAIGN` | Update Campaign | Tool to update an existing campaign's details by its id. use when you need to modify campaign attributes after creation. |
| `GIVEBUTTER_UPDATE_CONTACT` | Update Contact | Tool to update an existing contact's details by contact id. use when modifying contact information after confirming the contact id. only provided fields will be updated. |
| `GIVEBUTTER_UPDATE_WEBHOOK` | Update Webhook | Tool to update an existing webhook subscription's details. use when you need to modify a webhook's name, url, trigger events, or enabled state after confirming its id. example: "update webhook wh 1234567890 to point to https://example.com/hook, enable transaction.succeeded only." |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Givebutter MCP server is an implementation of the Model Context Protocol that connects your AI agent to Givebutter. It provides structured and secure access so your agent can perform Givebutter operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

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

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
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();
```

### 5. Initialize Composio client

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 Givebutter tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Givebutter 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 Givebutter tools as needed
```python
# Create Tool Router session for Givebutter
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['givebutter']
)

url = session.mcp.url
```

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

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "givebutter-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "givebutter-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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Givebutter 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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

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

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['givebutter']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "givebutter-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Givebutter related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
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: ['givebutter']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "givebutter-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 Givebutter 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 Givebutter 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.

## How to build Givebutter MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/givebutter/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/givebutter/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/givebutter/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/givebutter/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/givebutter/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/givebutter/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/givebutter/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/givebutter/framework/cli)
- [Google ADK](https://composio.dev/toolkits/givebutter/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/givebutter/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/givebutter/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/givebutter/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/givebutter/framework/crew-ai)

## Related Toolkits

- [Stripe](https://composio.dev/toolkits/stripe) - Stripe is a global online payments platform offering APIs for managing payments, customers, and subscriptions. Trusted by businesses for secure, efficient, and scalable payment processing worldwide.
- [Alpha vantage](https://composio.dev/toolkits/alpha_vantage) - Alpha Vantage is a financial data platform offering real-time and historical stock market APIs. Get instant, reliable access to equities, forex, and technical analysis data for smarter trading decisions.
- [Altoviz](https://composio.dev/toolkits/altoviz) - Altoviz is a cloud-based billing and invoicing platform for businesses. It streamlines online payments, expense tracking, and customizable invoice management.
- [Benzinga](https://composio.dev/toolkits/benzinga) - Benzinga provides real-time financial news and data APIs for market coverage. It helps you track breaking news and actionable market insights instantly.
- [Brex](https://composio.dev/toolkits/brex) - Brex provides corporate credit cards and spend management tailored for startups and tech businesses. It helps optimize company cash flow, streamline accounting, and accelerate business growth.
- [Chaser](https://composio.dev/toolkits/chaser) - Chaser is accounts receivable automation software that sends invoice reminders and helps businesses get paid faster. It streamlines the collections process to save time and improve cash flow.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Coinbase](https://composio.dev/toolkits/coinbase) - Coinbase is a platform for buying, selling, and storing cryptocurrency. It makes exchanging and managing crypto simple and secure for everyone.
- [Coinranking](https://composio.dev/toolkits/coinranking) - Coinranking is a comprehensive cryptocurrency market data platform offering access to real-time coin prices, market caps, and historical data. Get accurate, up-to-date stats for thousands of digital assets in one place.
- [Coupa](https://composio.dev/toolkits/coupa) - Coupa is a business spend management platform for procurement, invoicing, and expenses. It helps organizations streamline purchasing, control costs, and gain complete visibility over financial operations.
- [CurrencyScoop](https://composio.dev/toolkits/currencyscoop) - CurrencyScoop is a developer-friendly API for real-time and historical currency exchange rates. Easily access fiat and crypto data for smart, up-to-date financial applications.
- [Daffy](https://composio.dev/toolkits/daffy) - Daffy is a modern charitable giving platform with a donor-advised fund. Easily set aside funds, grow them tax-free, and donate to over 1.7 million U.S. charities.
- [Eagle doc](https://composio.dev/toolkits/eagle_doc) - Eagle doc is an AI-powered OCR API for invoices and receipts. It delivers fast, reliable, and accurate document data extraction for seamless automation.
- [Elorus](https://composio.dev/toolkits/elorus) - Elorus is an online invoicing and time-tracking software for freelancers and small businesses. Easily manage finances, bill clients, and track work in one place.
- [Eodhd apis](https://composio.dev/toolkits/eodhd_apis) - Eodhd apis delivers comprehensive financial data, including live and historical stock prices, via robust APIs. Easily access reliable, up-to-date market insights to power your apps, dashboards, and analytics.
- [Fidel api](https://composio.dev/toolkits/fidel_api) - Fidel api is a secure platform for linking payment cards to web and mobile apps. It enables real-time card transaction monitoring and event-based automation for businesses.
- [Finage](https://composio.dev/toolkits/finage) - Finage is a secure API platform delivering real-time and historical financial data for stocks, forex, crypto, indices, and commodities. It empowers developers and businesses to access, analyze, and act on market data instantly.
- [Finmei](https://composio.dev/toolkits/finmei) - Finmei is an invoicing tool that simplifies billing, invoice management, and expense tracking. Ideal for automating and organizing your business finances in one place.
- [Fixer](https://composio.dev/toolkits/fixer) - Fixer is a currency data API offering real-time and historical exchange rates for 170 currencies. Instantly access accurate, up-to-date forex data for your applications and workflows.
- [Fixer io](https://composio.dev/toolkits/fixer_io) - Fixer.io is a lightweight API for real-time and historical foreign exchange rates. It makes global currency conversion fast, accurate, and hassle-free.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Givebutter MCP?

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

### Can I use Tool Router MCP with LangChain?

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 Givebutter tools.

### Can I manage the permissions and scopes for Givebutter while using Tool Router?

Yes, absolutely. You can configure which Givebutter 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.

### How safe is my data with Composio Tool Router?

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 Givebutter data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)