How to integrate Fireberry MCP with LlamaIndex

This guide walks you through connecting Fireberry to LlamaIndex using the Composio tool router. By the end, you'll have a working Fireberry agent that can add new lead to contacts table, list all open deals in pipeline, fetch picklist options for deal stage through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Fireberry account through Composio's Fireberry MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Fireberry

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Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools.

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Introduction

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

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

Also integrate Fireberry with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI CrewAI

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 Fireberry
Connect LlamaIndex to the Fireberry MCP server
Build a Fireberry-powered agent using LlamaIndex
Interact with Fireberry 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 Fireberry MCP server, and what's possible with it?

The Fireberry MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fireberry CRM account. It provides structured and secure access to your CRM data, so your agent can perform actions like creating records, querying customer information, and managing picklists on your behalf.

Automated record creation: Let your agent swiftly add new entries to any Fireberry table, such as contacts, leads, or deals, using structured data you provide.
Smart CRM data retrieval: Ask your agent to query records with powerful filtering, sorting, and pagination—perfect for finding the exact customer or deal you need.
Picklist value management: Effortlessly fetch all available options for any picklist (dropdown) field, making data entry and workflow automation simpler and error-free.
Custom module support: Enable your agent to work with any Fireberry module, so you can handle specialized business processes or custom workflows.

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 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 Fireberry account and project
Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Fireberry

OpenAI API key (OPENAI_API_KEY)

Go to the OpenAI dashboard
Create an API key if you don't have one
Assign it to OPENAI_API_KEY in .env

Composio API key and user ID

Log into the Composio dashboard
Copy your API key from Settings
- Use this as COMPOSIO_API_KEY
Pick a stable user identifier (email or ID)
- Use this as COMPOSIO_USER_ID

Installing dependencies

npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv

Create a new Typescript project and install the necessary dependencies:

@composio/llamaindex: Composio's LlamaIndex integration
@llamaindex/openai: OpenAI LLM integration
@llamaindex/tools: MCP client for LlamaIndex
@llamaindex/workflow: Workflow framework for LlamaIndex
dotenv: Environment variable management

Set environment variables

bash

OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

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 Fireberry access

Import modules

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();

Create a new file called fireberry_llamaindex_agent.ts and import the required modules:

Key imports:

dotenv.config loads .env at runtime
readline gives us a simple CLI chat loop
Composio is the main Composio SDK client
mcp connects to an MCP endpoint
createAgent builds a LlamaIndex agent
openai configures the LLM backend

Load environment variables and initialize Composio

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");

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

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: ["fireberry"],
    },
  );

  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 Fireberry actions." ,
    llm,
    tools,
  });

  return agent;
}

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, fireberry)
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 Fireberry tools.
The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  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();
}

What's happening:

We're creating a direct terminal interface to chat with Fireberry
The LLM's responses are streamed to the CLI for faster interaction.
The agent uses context to maintain conversation history
The agent processes the request, selects appropriate Fireberry tools, and returns a result
We extract the answer from the result data structure and display it to the user
You can type 'quit' or 'exit' to stop the chat loop gracefully
Agent responses and any errors are streamed in a clear, readable format

Define the main entry point

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();

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 Fireberry

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Fireberry, then start asking questions.

Complete Code

Here's the complete code to get you started with Fireberry and LlamaIndex:

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: ["fireberry"],
    },
  );

  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 Fireberry actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  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 Fireberry to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:

Tool Router dynamically exposes Fireberry 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.

TOOLS

Supported Tools

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

Create a Competitor

Tool to create a new competitor in Fireberry.

Create a Fireberry contact

Tool to create a new contact in Fireberry CRM.

Create an Activity Log

Create a new Activity Log record in Fireberry.

Create a date field

Tool to create a new date field in a Fireberry object/table.

Create a Fireberry lookup field

Tool to create a lookup field in Fireberry CRM.

Create a new Fireberry account

Tool to create a new account in Fireberry CRM.

Create an Article

Tool to create a new article in Fireberry.

Create a Fireberry asset

Creates a new asset (account product) in Fireberry.

Create an Opportunity

Tool to create a new opportunity in Fireberry CRM.

Create an Order Item

Tool to create a new order item in Fireberry CRM.

Create a note

Create a new note record in Fireberry.

Create a phone call

Creates a new phone call record in Fireberry's call log.

Create a Fireberry product

Tool to create a new product in Fireberry.

Create a Project

Tool to create a new project in Fireberry CRM.

Create a Task

Tool to create a new task in Fireberry CRM.

Create a Ticket

Tool to create a new ticket (case) in Fireberry CRM.

Create a URL field

Tool to create a new URL field in a Fireberry object/table.

Create a Campaign

Tool to create a new campaign in Fireberry.

Create a CRM Order

Tool to create a new CRM Order in Fireberry.

Upload file to Fireberry record

Tool to upload a file to a specific record in Fireberry.

Create a Fireberry meeting

Tool to create a new meeting (activity) in Fireberry.

Create a new Fireberry record

Creates a new record in a specified Fireberry table/module.

Delete an Account

Tool to delete an account from Fireberry using its GUID.

Delete a Competitor

Tool to delete a competitor in Fireberry by its GUID.

Delete a contract

Tool to delete a contract in Fireberry by its GUID.

Delete an Activity Log

Delete an activity log by its GUID.

Delete a custom field

Tool to delete a custom field from a Fireberry object/table.

Delete an Article

Tool to delete an article from Fireberry by its GUID.

Delete a Fireberry asset

Delete an asset from Fireberry by its unique identifier.

Delete an Opportunity

Tool to delete an opportunity in Fireberry by its GUID.

Delete an Order Item

Tool to delete an order item in Fireberry by its GUID.

Delete a Note

Tool to delete a note from Fireberry using its GUID.

Delete a Phone Call

Tool to delete a phone call record from Fireberry using its GUID.

Delete a project

Tool to delete a project from Fireberry using its GUID.

Delete a task

Tool to delete a task in Fireberry by its GUID.

Delete a ticket

Tool to delete a ticket (case) from Fireberry using its GUID.

Delete a Business Unit

Tool to delete a Business Unit in Fireberry using its GUID.

Delete a Fireberry campaign

Tool to delete a campaign from Fireberry.

Delete a Contact

Tool to delete a contact from Fireberry using its GUID.

Delete a CRM User

Tool to delete a CRM user from Fireberry using its GUID.

Delete a Meeting

Tool to delete a meeting activity from Fireberry by its GUID.

Delete a product

Tool to delete a product in Fireberry by its GUID.

Get an Account

Tool to retrieve a specific account record by its GUID.

Get a CRM Order

Tool to retrieve a specific CRM Order from Fireberry by its GUID.

Get All Accounts

Tool to retrieve all accounts from Fireberry CRM with pagination support.

Get All Activity Logs (v2)

Tool to retrieve all activity logs from Fireberry using v2 API endpoint with pagination support.

Get all articles from Fireberry

Tool to retrieve all articles from Fireberry with pagination support.

Get All Assets

Tool to retrieve all assets (account products) from Fireberry with pagination support.

Get All Business Units (v2)

Tool to retrieve all business units from Fireberry using v2 API endpoint with pagination support.

Get All Campaigns

Tool to retrieve all campaigns from Fireberry with pagination support.

Get All Competitors (v2)

Tool to retrieve all competitors from Fireberry with pagination support.

Get All Contacts

Tool to retrieve all contacts from Fireberry with pagination support.

Get All Contracts

Tool to retrieve all contracts from Fireberry with pagination support.

Get All Custom Object Records

Tool to retrieve all records from a specified custom object in Fireberry with pagination support.

Get All Meetings

Tool to retrieve all meetings (activities) from Fireberry CRM with pagination support.

Get All Notes (Detailed)

Tool to retrieve all notes from Fireberry with detailed field schema and pagination support.

Get All Objects

Tool to retrieve all object type metadata from Fireberry.

Get All Order Items

Tool to retrieve all order items from Fireberry with pagination support.

Get All Orders

Tool to retrieve all orders from Fireberry with pagination support.

Get All Phone Calls

Tool to retrieve all phone call records from Fireberry with pagination support.

Get All Projects (v2)

Tool to retrieve all projects from Fireberry with pagination support.

Get All Tasks

Tool to retrieve all tasks from Fireberry with pagination support.

Get All Tickets

Tool to retrieve all ticket records (cases) from Fireberry with pagination support.

Get All Users

Tool to retrieve all CRM users from Fireberry with pagination support.

Get a Meeting

Tool to retrieve a specific meeting/activity record by its unique identifier (GUID).

Get an Activity Log

Tool to retrieve a specific activity log record from Fireberry by its GUID.

Get an Article

Tool to retrieve a specific article from Fireberry by its GUID.

Get an Asset

Tool to retrieve a specific asset record by its GUID.

Get an Object

Tool to retrieve metadata for a specific object by its ID.

Get an Object's Fields

Tool to retrieve metadata about fields for a specific object type in Fireberry.

Get an Opportunity

Tool to retrieve a specific opportunity record by its GUID.

Get an Order Item

Tool to retrieve a specific order item record by its GUID.

Get a Note

Tool to retrieve a specific note record by its GUID.

Get a phone call record

Tool to retrieve a specific phone call record from Fireberry by its GUID.

Get a Product

Tool to retrieve a specific product record by its GUID.

Get a Project

Tool to retrieve a specific project from Fireberry by its GUID.

Get a Task

Tool to retrieve a specific task record by its GUID.

Get a Ticket

Tool to retrieve a specific ticket (case) record by its GUID.

Get Campaign by ID

Tool to retrieve a single campaign by its GUID.

Get a Competitor

Tool to retrieve a specific competitor record by its GUID.

Get a Contact

Tool to retrieve a specific contact record by its GUID.

Get Custom Object Record

Tool to retrieve a specific custom object record by its GUID and object code.

Get Field Details

Tool to retrieve detailed metadata for a specific field in a Fireberry object/table.

Get Object Field Values

Tool to retrieve picklist field values from the metadata endpoint.

Get Items for an Order

Tool to retrieve all items for a specific order from Fireberry.

Get Picklist Field Values

Tool to retrieve picklist field values from Fireberry metadata API.

Get Picklist Values

Tool to retrieve all possible picklist (dropdown) values for a specific field by querying records and extracting unique values.

Get Related Records

Tool to retrieve related records for a specific object in Fireberry.

Get Fireberry Task by ID

Tool to retrieve a single task record by its unique ID (GUID).

Get a Fireberry user by ID

Tool to retrieve a single user by their unique ID from Fireberry.

List All Opportunities

Tool to retrieve all opportunities from Fireberry CRM with pagination support.

List All Products

Tool to retrieve all products from Fireberry CRM with pagination support.

Fireberry: Query Records

Query and retrieve records from a Fireberry module with optional filtering, sorting, and pagination.

Query Fireberry records with filters

Query records in any Fireberry object with advanced filtering, sorting, and pagination.

Update a Business Unit

Tool to update an existing business unit in Fireberry.

Update Fireberry Account

Updates an existing account record in Fireberry with new field values.

Update a Fireberry Competitor

Updates an existing competitor record in Fireberry by GUID.

Update a Fireberry contact

Tool to update an existing contact in Fireberry CRM.

Update a Contract

Tool to update an existing contract in Fireberry.

Update an Activity Log

Update an existing Activity Log record in Fireberry.

Update a Date Field

Tool to update a date field configuration in Fireberry.

Update a Date & Time Field

Tool to update a Date & Time field's properties in Fireberry.

Update a Formula Field

Tool to update a formula field in Fireberry CRM.

Update an HTML Field

Tool to update an HTML field configuration in Fireberry.

Update a Fireberry Meeting

Tool to update an existing meeting (activity) in Fireberry.

Update a Fireberry article

Updates an existing article in Fireberry.

Update an Asset

Update an existing asset (accountproduct) in Fireberry.

Update an Email Address Field

Tool to update the configuration of an email address field in Fireberry.

Update an Opportunity

Tool to update an existing opportunity in Fireberry CRM.

Update an Order Item

Tool to update an existing order item in Fireberry.

Update a Number Field

Tool to update a number field configuration in Fireberry.

Update a Phone Number Field

Tool to update a phone number field configuration in Fireberry.

Update a Product

Tool to update an existing product in Fireberry.

Update a Project

Tool to update an existing project in Fireberry CRM.

Update a Text Area Field

Tool to update a Text Area field's properties in Fireberry.

Update a Text Field

Tool to update a text field configuration in Fireberry.

Update a Ticket

Tool to update an existing ticket (case) in Fireberry.

Update a URL Field

Tool to update a URL field configuration in Fireberry.

Update a User

Tool to update an existing user in Fireberry CRM.

Update a Fireberry Campaign

Tool to update an existing campaign in Fireberry by its GUID.

Update a CRM Order

Tool to update an existing CRM order in Fireberry.

Update a phone call record

Tool to update an existing phone call record in Fireberry.

Update a Task (V2)

Tool to update an existing task using Fireberry v2 API.

FRAMEWORKS

How to build Fireberry MCP Agent with another framework

OpenAI Agents SDK

Use Fireberry MCP with OpenAI Agents SDK

Claude Agent SDK

Use Fireberry MCP with Claude Agent SDK

Claude Code

Use Fireberry MCP with Claude Code

Claude Cowork

Use Fireberry MCP with Claude Cowork

Codex

Use Fireberry MCP with Codex

OpenClaw

Use Fireberry MCP with OpenClaw

Hermes

Use Fireberry MCP with Hermes

CLI

Use Fireberry MCP with CLI

Google ADK

Use Fireberry MCP with Google ADK

LangChain

Use Fireberry MCP with LangChain

Vercel AI SDK

Use Fireberry MCP with Vercel AI SDK

Mastra AI

Use Fireberry MCP with Mastra AI

CrewAI

Use Fireberry MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Hubspot

Oauth2Api Key

HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place.

Pipedrive

Oauth2Api Key

Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up.

Salesforce

Oauth2S2s Oauth2

Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships.

Apollo

Api Key

Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place.

FAQ

Frequently asked questions

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

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 Fireberry tools.

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

Start with Fireberry.It takes 30 seconds.

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

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Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

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