# How to integrate Brevo MCP with LlamaIndex ```json { "title": "How to integrate Brevo MCP with LlamaIndex", "toolkit": "Brevo", "toolkit_slug": "brevo", "framework": "LlamaIndex", "framework_slug": "llama-index", "url": "https://composio.dev/toolkits/brevo/framework/llama-index", "markdown_url": "https://composio.dev/toolkits/brevo/framework/llama-index.md", "updated_at": "2026-05-12T10:04:03.619Z" } ``` ## Introduction This guide walks you through connecting Brevo to LlamaIndex using the Composio tool router. By the end, you'll have a working Brevo agent that can send sms campaign to new subscribers, create or update an email template, find contact details by email address through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Brevo account through Composio's Brevo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Brevo with - [OpenAI Agents SDK](https://composio.dev/toolkits/brevo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/brevo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/brevo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/brevo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/brevo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/brevo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/brevo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/brevo/framework/cli) - [Google ADK](https://composio.dev/toolkits/brevo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/brevo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/brevo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/brevo/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/brevo/framework/crew-ai) ## TL;DR Here's what you'll learn: - Set your OpenAI and Composio API keys - Install LlamaIndex and Composio packages - Create a Composio Tool Router session for Brevo - Connect LlamaIndex to the Brevo MCP server - Build a Brevo-powered agent using LlamaIndex - Interact with Brevo through natural language ## What is LlamaIndex? LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools. Key features include: - ReAct Agent: Reasoning and acting pattern for tool-using agents - MCP Tools: Native support for Model Context Protocol - Context Management: Maintain conversation context across interactions - Async Support: Built for async/await patterns ## What is the Brevo MCP server, and what's possible with it? The Brevo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Brevo account. It provides structured and secure access to your email, SMS marketing, automation, and contact management tools, so your agent can perform actions like sending campaigns, managing contacts, creating templates, and retrieving account details on your behalf. - Automated campaign management: Let your agent create, schedule, or delete SMS campaigns, including customizing recipients, sender details, and campaign content. - Contact and company management: Easily add new contacts or companies, update existing records, or remove outdated ones to keep your database organized and up to date. - Email template automation: Empower your agent to create, update, or delete email templates for consistent and efficient campaign design and execution. - Account information retrieval: Ask your agent to fetch detailed account information, including plan details, credits, and profile data, for easy monitoring and reporting. - Contact search and segmentation: Have your agent search for specific contacts or retrieve segmented contact lists based on filters like creation date, list IDs, or attributes. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BREVO_CREATE_A_COMPANY` | Create a company | Creates a new company record in your Brevo CRM. Companies can be used to organize contacts and deals, track business relationships, and manage customer accounts. You can add custom attributes, link existing contacts and deals, and set country codes for international phone numbers. Use this when you need to add a new business or organization to your CRM system. | | `BREVO_CREATE_CONTACT_LIST` | Create Contact List | Creates a new contact list (audience) in Brevo within a specified folder. Contact lists are used to organize and segment contacts for email campaigns, SMS campaigns, and marketing automation workflows. Use this tool when you need to: - Create a new audience segment for a marketing campaign - Organize contacts by specific criteria (e.g., geographic location, interests, purchase history) - Set up a list for newsletter subscribers, event attendees, or customer segments - Prepare a target audience before adding contacts or launching campaigns Note: You must specify a valid folder ID. Use Get Contact Lists to view existing folders and their IDs. | | `BREVO_CREATE_OR_UPDATE_EMAIL_TEMPLATE` | Create or Update Email Template | This tool creates a new email template or updates an existing one in Brevo. If a 'templateId' is provided, it performs an update; otherwise, it creates a new template. | | `BREVO_CREATE_SMS_CAMPAIGN` | Create SMS Campaign | This tool allows you to create a new SMS campaign in Brevo. You can specify the campaign name, sender, content, recipients (by providing list IDs, exclusion list IDs, or segment IDs), and optionally schedule the campaign for a specific time. You can also enable Unicode characters, add an organization prefix, and include unsubscribe instructions. | | `BREVO_DELETE_COMPANY` | Delete a company | Deletes a company from Brevo using its unique identifier. | | `BREVO_DELETE_CONTACT` | Delete Contact | Deletes a contact from Brevo by email, contact ID, external ID, phone number, WhatsApp ID, or landline number. Use the identifier_type parameter to specify the type of identifier when using ext_id, phone_id, whatsapp_id, or landline_number_id. | | `BREVO_DELETE_EMAIL_TEMPLATE` | Delete Email Template | This tool deletes an inactive email template from Brevo. You need to provide the 'templateId' of the email template you want to delete. Only inactive templates can be deleted. | | `BREVO_DELETE_SMS_CAMPAIGN` | Delete SMS Campaign | This tool deletes an existing SMS campaign. | | `BREVO_GET_ACCOUNT_INFO` | Get Account Information | Retrieves comprehensive information about the authenticated Brevo account. Returns account details including: - Account holder information (email, first name, last name, company name) - Complete address (street, city, zip code, country) - Plan details with credit information (type, credits remaining, start/end dates) - Relay configuration for transactional emails (enabled status and data) - Marketing Automation status and tracker key (if enabled) No input parameters are required - the action uses the authenticated account's credentials. Use this action to: - Verify account configuration and settings - Check available credits and plan type - Monitor transactional email relay status - Retrieve Marketing Automation tracker information. If credentials are missing or invalid, verify the Brevo connection is active before calling — retries will not resolve credential issues. If blocked by an 'unrecognised IP address' error, add the integration host's IP to the Brevo account allowlist. | | `BREVO_GET_ALL_CONTACTS` | Get all contacts | This tool retrieves all contacts from your Brevo account with pagination and filtering based on modification/creation dates, list IDs, segment IDs, and contact attributes. For complete retrieval, iterate pages by incrementing `offset` by `limit` on each call until no more records are returned; a single call returns at most `limit` contacts. | | `BREVO_GET_ALL_EMAIL_TEMPLATES` | Get all email templates | This tool retrieves a list of all email templates created in your Brevo account. It corresponds to the GET /v3/smtp/templates endpoint as per the Brevo API documentation, with optional parameters for filtering (templateStatus), pagination (limit, offset), and sorting (asc/desc). | | `BREVO_GET_ALL_SENDERS` | Get All Senders | This tool retrieves a list of all senders associated with the Brevo account. Senders are the email addresses or domains that are authorized to send emails through Brevo. This action can be useful for managing and verifying sender identities. | | `BREVO_GET_COMPANY_DETAILS` | Get Company Details | Retrieves detailed information about a specific company from Brevo's CRM. Returns company data including its unique identifier, custom attributes, and lists of linked contact IDs and deal IDs. This is useful for accessing comprehensive company records and understanding company relationships. | | `BREVO_GET_CONTACT_DETAILS` | Get Contact Details | This tool retrieves detailed information about a specific contact in Brevo. You can identify the contact using their email address (URL-encoded), their unique contact ID, or their SMS attribute value. | | `BREVO_GET_CONTACT_LISTS` | Get contact lists | Retrieves all contact lists from your Brevo account with pagination support. Returns list IDs, names, subscriber counts, and folder associations. Use this to discover available lists or obtain list IDs needed for other operations (e.g., SMS campaigns, adding contacts to lists). | | `BREVO_GET_EMAIL_CAMPAIGN_DETAILS` | Get Email Campaign Details | Tool to retrieve full configuration and content for a specific email campaign. Use when you need complete campaign details including HTML content, recipients, statistics, and all configuration settings that may be omitted from list responses. | | `BREVO_GET_SMS_CAMPAIGN_DETAILS` | Get SMS Campaign Details | Retrieves the details of a specific SMS campaign. This action fetches complete information about an SMS campaign including its status, content, sender, scheduling, recipients, and statistics. | | `BREVO_GET_SMS_CAMPAIGNS` | Get SMS Campaigns | Retrieves all SMS campaigns from your Brevo account with optional filtering and pagination. Use this tool to: - List all SMS campaigns with their details (name, status, content, sender, dates) - Filter campaigns by status (sent, draft, queued, suspended, inProcess, archive) - Filter sent campaigns by date range - Control pagination with limit and offset - Sort results by creation date (ascending or descending) Returns campaign overview information including ID, name, status, content, sender, scheduled date (if any), and creation/modification timestamps. | | `BREVO_LIST_ALL_COMPANIES` | List All Companies | This action retrieves a list of all companies stored in the Brevo CRM. It supports pagination and filtering by name and other attributes. | | `BREVO_LIST_EMAIL_CAMPAIGNS` | List Email Campaigns | This tool retrieves a list of all email campaigns associated with the user's Brevo account. It allows filtering by campaign type, status, start date, and end date. The response includes the total count of campaigns and an array of campaign objects, each containing details like ID, name, subject, type, status, scheduled date/time, sender information, and optionally, campaign statistics. A response with `count` of 0 and an empty campaigns array is a valid result, not an error. | | `BREVO_UPDATE_EMAIL_CAMPAIGN` | Update Email Campaign | Updates an email campaign in Brevo using its unique identifier. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Brevo MCP server is an implementation of the Model Context Protocol that connects your AI agent to Brevo. It provides structured and secure access so your agent can perform Brevo 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 Before you begin, make sure you have: - Python 3.8/Node 16 or higher installed - A Composio account with the API key - An OpenAI API key - A Brevo account and project - Basic familiarity with async Python/Typescript ### 1. Getting API Keys for OpenAI, Composio, and Brevo No description provided. ### 2. Installing dependencies No description provided. ```python pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv ``` ```typescript npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv ``` ### 3. Set environment variables Create a .env file in your project root: These credentials will be used to: - Authenticate with OpenAI's GPT-5 model - Connect to Composio's Tool Router - Identify your Composio user session for Brevo access ```bash OPENAI_API_KEY=your-openai-api-key COMPOSIO_API_KEY=your-composio-api-key COMPOSIO_USER_ID=your-user-id ``` ### 4. Import modules No description provided. ```python import asyncio import os import dotenv from composio import Composio from composio_llamaindex import LlamaIndexProvider from llama_index.core.agent.workflow import ReActAgent from llama_index.core.workflow import Context from llama_index.llms.openai import OpenAI from llama_index.tools.mcp import BasicMCPClient, McpToolSpec dotenv.load_dotenv() ``` ```typescript import "dotenv/config"; import readline from "node:readline/promises"; import { stdin as input, stdout as output } from "node:process"; import { Composio } from "@composio/core"; import { mcp } from "@llamaindex/tools"; import { agent as createAgent } from "@llamaindex/workflow"; import { openai } from "@llamaindex/openai"; dotenv.config(); ``` ### 5. Load environment variables and initialize Composio No description provided. ```python OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not OPENAI_API_KEY: raise ValueError("OPENAI_API_KEY is not set in the environment") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set in the environment") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set in the environment") ``` ```typescript const OPENAI_API_KEY = process.env.OPENAI_API_KEY; const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY; const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID; if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set"); if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set"); ``` ### 6. Create a Tool Router session and build the agent function What's happening here: - We create a Composio client using your API key and configure it with the LlamaIndex provider - We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, brevo) - The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools - LlamaIndex will connect to this endpoint to dynamically discover and use the available Brevo tools. - The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent. ```python async def build_agent() -> ReActAgent: composio_client = Composio( api_key=COMPOSIO_API_KEY, provider=LlamaIndexProvider(), ) session = composio_client.create( user_id=COMPOSIO_USER_ID, toolkits=["brevo"], ) mcp_url = session.mcp.url print(f"Composio MCP URL: {mcp_url}") mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY}) mcp_tool_spec = McpToolSpec(client=mcp_client) tools = await mcp_tool_spec.to_tool_list_async() llm = OpenAI(model="gpt-5") description = "An agent that uses Composio Tool Router MCP tools to perform Brevo actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Brevo actions. """ return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True) ``` ```typescript async function buildAgent() { console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`); console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`); const composio = new Composio({ apiKey: COMPOSIO_API_KEY, provider: new LlamaindexProvider(), }); const session = await composio.create( COMPOSIO_USER_ID!, { toolkits: ["brevo"], }, ); const mcpUrl = session.mcp.url; console.log(`Composio Tool Router MCP URL: ${mcpUrl}`); const server = mcp({ url: mcpUrl, clientName: "composio_tool_router_with_llamaindex", requestInit: { headers: { "x-api-key": COMPOSIO_API_KEY!, }, }, // verbose: true, }); const tools = await server.tools(); const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" }); const agent = createAgent({ name: "composio_tool_router_with_llamaindex", description : "An agent that uses Composio Tool Router MCP tools to perform actions.", systemPrompt: "You are a helpful assistant connected to Composio Tool Router."+ "Use the available tools to answer user queries and perform Brevo actions." , llm, tools, }); return agent; } ``` ### 7. Create an interactive chat loop No description provided. ```python async def chat_loop(agent: ReActAgent) -> None: ctx = Context(agent) print("Type 'quit', 'exit', or Ctrl+C to stop.") while True: try: user_input = input("\nYou: ").strip() except (KeyboardInterrupt, EOFError): print("\nBye!") break if not user_input or user_input.lower() in {"quit", "exit"}: print("Bye!") break try: print("Agent: ", end="", flush=True) handler = agent.run(user_input, ctx=ctx) async for event in handler.stream_events(): # Stream token-by-token from LLM responses if hasattr(event, "delta") and event.delta: print(event.delta, end="", flush=True) # Show tool calls as they happen elif hasattr(event, "tool_name"): print(f"\n[Using tool: {event.tool_name}]", flush=True) # Get final response response = await handler print() # Newline after streaming except KeyboardInterrupt: print("\n[Interrupted]") continue except Exception as e: print(f"\nError: {e}") ``` ```typescript async function chatLoop(agent: ReturnType) { const rl = readline.createInterface({ input, output }); console.log("Type 'quit' or 'exit' to stop."); while (true) { let userInput: string; try { userInput = (await rl.question("\nYou: ")).trim(); } catch { console.log("\nAgent: Bye!"); break; } if (!userInput) { continue; } const lower = userInput.toLowerCase(); if (lower === "quit" || lower === "exit") { console.log("Agent: Bye!"); break; } try { process.stdout.write("Agent: "); const stream = agent.runStream(userInput); let finalResult: any = null; for await (const event of stream) { // The event.data contains the streamed content const data: any = event.data; // Check for streaming delta content if (data?.delta) { process.stdout.write(data.delta); } // Store final result for fallback if (data?.result || data?.message) { finalResult = data; } } // If no streaming happened, show the final result if (finalResult) { const answer = finalResult.result ?? finalResult.message?.content ?? finalResult.message ?? ""; if (answer && typeof answer === "string" && !answer.includes("[object")) { process.stdout.write(answer); } } console.log(); // New line after streaming completes } catch (err: any) { console.error("\nAgent error:", err?.message ?? err); } } rl.close(); } ``` ### 8. Define the main entry point What's happening here: - We're orchestrating the entire application flow - The agent gets built with proper error handling - Then we kick off the interactive chat loop so you can start talking to Brevo ```python async def main() -> None: agent = await build_agent() await chat_loop(agent) if __name__ == "__main__": # Handle Ctrl+C gracefully signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0))) try: asyncio.run(main()) except KeyboardInterrupt: print("\nBye!") ``` ```typescript async function main() { try { const agent = await buildAgent(); await chatLoop(agent); } catch (err) { console.error("Failed to start agent:", err); process.exit(1); } } main(); ``` ### 9. Run the agent When prompted, authenticate and authorise your agent with Brevo, then start asking questions. ```bash python llamaindex_agent.py ``` ```typescript npx ts-node llamaindex-agent.ts ``` ## Complete Code ```python import asyncio import os import signal import dotenv from composio import Composio from composio_llamaindex import LlamaIndexProvider from llama_index.core.agent.workflow import ReActAgent from llama_index.core.workflow import Context from llama_index.llms.openai import OpenAI from llama_index.tools.mcp import BasicMCPClient, McpToolSpec dotenv.load_dotenv() OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not OPENAI_API_KEY: raise ValueError("OPENAI_API_KEY is not set") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") async def build_agent() -> ReActAgent: composio_client = Composio( api_key=COMPOSIO_API_KEY, provider=LlamaIndexProvider(), ) session = composio_client.create( user_id=COMPOSIO_USER_ID, toolkits=["brevo"], ) mcp_url = session.mcp.url print(f"Composio MCP URL: {mcp_url}") mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY}) mcp_tool_spec = McpToolSpec(client=mcp_client) tools = await mcp_tool_spec.to_tool_list_async() llm = OpenAI(model="gpt-5") description = "An agent that uses Composio Tool Router MCP tools to perform Brevo actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Brevo actions. """ return ReActAgent( tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True, ); async def chat_loop(agent: ReActAgent) -> None: ctx = Context(agent) print("Type 'quit', 'exit', or Ctrl+C to stop.") while True: try: user_input = input("\nYou: ").strip() except (KeyboardInterrupt, EOFError): print("\nBye!") break if not user_input or user_input.lower() in {"quit", "exit"}: print("Bye!") break try: print("Agent: ", end="", flush=True) handler = agent.run(user_input, ctx=ctx) async for event in handler.stream_events(): # Stream token-by-token from LLM responses if hasattr(event, "delta") and event.delta: print(event.delta, end="", flush=True) # Show tool calls as they happen elif hasattr(event, "tool_name"): print(f"\n[Using tool: {event.tool_name}]", flush=True) # Get final response response = await handler print() # Newline after streaming except KeyboardInterrupt: print("\n[Interrupted]") continue except Exception as e: print(f"\nError: {e}") async def main() -> None: agent = await build_agent() await chat_loop(agent) if __name__ == "__main__": # Handle Ctrl+C gracefully signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0))) try: asyncio.run(main()) except KeyboardInterrupt: print("\nBye!") ``` ```typescript import "dotenv/config"; import readline from "node:readline/promises"; import { stdin as input, stdout as output } from "node:process"; import { Composio } from "@composio/core"; import { LlamaindexProvider } from "@composio/llamaindex"; import { mcp } from "@llamaindex/tools"; import { agent as createAgent } from "@llamaindex/workflow"; import { openai } from "@llamaindex/openai"; dotenv.config(); const OPENAI_API_KEY = process.env.OPENAI_API_KEY; const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY; const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID; if (!OPENAI_API_KEY) { throw new Error("OPENAI_API_KEY is not set in the environment"); } if (!COMPOSIO_API_KEY) { throw new Error("COMPOSIO_API_KEY is not set in the environment"); } if (!COMPOSIO_USER_ID) { throw new Error("COMPOSIO_USER_ID is not set in the environment"); } async function buildAgent() { console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`); console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`); const composio = new Composio({ apiKey: COMPOSIO_API_KEY, provider: new LlamaindexProvider(), }); const session = await composio.create( COMPOSIO_USER_ID!, { toolkits: ["brevo"], }, ); const mcpUrl = session.mcp.url; console.log(`Composio Tool Router MCP URL: ${mcpUrl}`); const server = mcp({ url: mcpUrl, clientName: "composio_tool_router_with_llamaindex", requestInit: { headers: { "x-api-key": COMPOSIO_API_KEY!, }, }, // verbose: true, }); const tools = await server.tools(); const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" }); const agent = createAgent({ name: "composio_tool_router_with_llamaindex", description: "An agent that uses Composio Tool Router MCP tools to perform actions.", systemPrompt: "You are a helpful assistant connected to Composio Tool Router."+ "Use the available tools to answer user queries and perform Brevo actions." , llm, tools, }); return agent; } async function chatLoop(agent: ReturnType) { const rl = readline.createInterface({ input, output }); console.log("Type 'quit' or 'exit' to stop."); while (true) { let userInput: string; try { userInput = (await rl.question("\nYou: ")).trim(); } catch { console.log("\nAgent: Bye!"); break; } if (!userInput) { continue; } const lower = userInput.toLowerCase(); if (lower === "quit" || lower === "exit") { console.log("Agent: Bye!"); break; } try { process.stdout.write("Agent: "); const stream = agent.runStream(userInput); let finalResult: any = null; for await (const event of stream) { // The event.data contains the streamed content const data: any = event.data; // Check for streaming delta content if (data?.delta) { process.stdout.write(data.delta); } // Store final result for fallback if (data?.result || data?.message) { finalResult = data; } } // If no streaming happened, show the final result if (finalResult) { const answer = finalResult.result ?? finalResult.message?.content ?? finalResult.message ?? ""; if (answer && typeof answer === "string" && !answer.includes("[object")) { process.stdout.write(answer); } } console.log(); // New line after streaming completes } catch (err: any) { console.error("\nAgent error:", err?.message ?? err); } } rl.close(); } async function main() { try { const agent = await buildAgent(); await chatLoop(agent); } catch (err: any) { console.error("Failed to start agent:", err?.message ?? err); process.exit(1); } } main(); ``` ## Conclusion You've successfully connected Brevo to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways: - Tool Router dynamically exposes Brevo tools through an MCP endpoint - LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations - The agent becomes more capable without increasing prompt size - Async Python provides clean, efficient execution of agent workflows You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter. ## How to build Brevo MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/brevo/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/brevo/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/brevo/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/brevo/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/brevo/framework/codex) - [OpenClaw](https://composio.dev/toolkits/brevo/framework/openclaw) - [Hermes](https://composio.dev/toolkits/brevo/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/brevo/framework/cli) - [Google ADK](https://composio.dev/toolkits/brevo/framework/google-adk) - [LangChain](https://composio.dev/toolkits/brevo/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/brevo/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/brevo/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/brevo/framework/crew-ai) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools. - [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. - [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals. - [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams. - [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience. - [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs. - [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics. - [Doppler marketing automation](https://composio.dev/toolkits/doppler_marketing_automation) - Doppler marketing automation is a platform for creating, sending, and tracking email campaigns. It helps you automate marketing workflows and manage subscriber lists for better engagement. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Brevo MCP? With a standalone Brevo MCP server, the agents and LLMs can only access a fixed set of Brevo tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Brevo and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with LlamaIndex? Yes, you can. LlamaIndex 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 Brevo tools. ### Can I manage the permissions and scopes for Brevo while using Tool Router? Yes, absolutely. You can configure which Brevo 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 Brevo data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)