How to integrate Faraday MCP with LlamaIndex

This guide walks you through connecting Faraday to LlamaIndex using the Composio tool router. By the end, you'll have a working Faraday agent that can enrich salesforce leads with predictive insights, automate email categorization using faraday ai, trigger customer follow-up based on faraday scores through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Faraday account through Composio's Faraday MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Introduction

This guide walks you through connecting Faraday to LlamaIndex using the Composio tool router. By the end, you'll have a working Faraday agent that can enrich salesforce leads with predictive insights, automate email categorization using faraday ai, trigger customer follow-up based on faraday scores through natural language commands.

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

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

Also integrate Faraday with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AICrewAI

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

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

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

What is Composio SDK?

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

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

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

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

Step-by-step Guide

Step by step10 STEPS
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 Faraday account and project
  • Basic familiarity with async Python/Typescript
2

Getting API Keys for OpenAI, Composio, and Faraday

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
3

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
4

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 Faraday access
5

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 faraday_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
6

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.

7

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: ["faraday"],
    },
  );

  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 Faraday 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, faraday)
  • 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 Faraday tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
8

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 Faraday
  • 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 Faraday 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
9

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 Faraday
10

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

Here's the complete code to get you started with Faraday 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: ["faraday"],
    },
  );

  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 Faraday 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 Faraday to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Faraday 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 Faraday action and event your agent gets out of the box.

Archive Cohort

Tool to archive a cohort in Faraday.

Archive Connection

Tool to archive a connection in Faraday.

Archive Dataset

Tool to archive a dataset in Faraday.

Archive Outcome

Tool to archive an outcome in Faraday.

Archive Persona Set

Tool to archive a persona set in Faraday.

Archive Place

Tool to archive a place in Faraday.

Archive Scope

Tool to archive a scope in Faraday.

Archive Stream

Tool to archive a stream in Faraday.

Archive Target

Tool to archive a target in Faraday.

Archive Trait

Tool to archive a trait in Faraday.

Create Account

Tool to create a new Faraday account with specified name and branding.

Create Cohorts

Tool to create a new cohort in Faraday.

Create Dataset

Tool to create a new dataset in Faraday.

Create Outcome

Tool to create a new outcome.

Create Persona Set

Tool to create a new persona set.

Create Place

Tool to create a new place in Faraday.

Create Scope

Tool to create a new scope in Faraday.

Create Stream

Tool to create a new stream or find an existing stream by name.

Create Target Preview

Tool to start a preview delivery for a target.

Create Target

Tool to create a target in Faraday.

Create Trait

Tool to create a new trait in Faraday.

Create Webhook Endpoint

Tool to create a new webhook endpoint.

Delete Account

Tool to delete an account by its UUID.

Delete All Orphaned Traits

Tool to delete all orphaned traits from Faraday.

Delete Cohort

Tool to permanently delete a cohort from Faraday.

Delete Connection

Tool to delete a Faraday connection by its UUID.

Delete Dataset

Tool to delete a dataset from Faraday.

Delete Outcome

Tool to delete an outcome by its UUID.

Delete Persona Set

Tool to delete a persona set.

Delete Place

Tool to delete a place by its UUID.

Delete Scope

Tool to delete a scope by its UUID.

Delete Stream

Tool to delete a stream by its UUID or name.

Delete Target

Tool to delete a target by its UUID.

Delete Upload

Permanently deletes a file from a Faraday dataset directory.

Delete Webhook Endpoint

Tool to delete a webhook endpoint by its UUID.

Force Update Cohort

Tool to trigger a rerun for a cohort.

Force Update Connection

Tool to trigger a rerun for a Faraday connection.

Force Update Dataset

Tool to trigger a rerun for a dataset.

Force Update Outcome

Tool to trigger a rerun for an outcome resource.

Force Update Persona Set

Tool to trigger a rerun for a persona set resource.

Force Update Place

Tool to trigger a rerun for a place.

Force Update Scope

Tool to trigger a rerun for a scope resource.

Force Update Stream

Tool to trigger a rerun for a stream.

Force Update Target

Tool to trigger a rerun for a target.

Force Update Trait

Tool to trigger a rerun for a trait.

Get Account

Tool to retrieve detailed information about a Faraday account by its UUID.

List Accounts

Tool to list all Faraday accounts accessible by the current user.

Get Accounts Billing

Tool to get billing information about your account.

Get Cohort

Tool to retrieve a specific cohort by ID.

Get Cohort Membership Analysis

Tool to get cohort membership counts over time for a specific cohort.

List Cohorts

Tool to list all cohorts in your Faraday account.

Get Connection Datasets

Tool to retrieve all datasets that use a specific connection.

Get Connection Targets

Tool to retrieve all targets that use a specific connection.

Get Current Account

Tool to retrieve the current account information.

Get Current Account Billing

Tool to retrieve billing information about the current account.

Get Dataset

Tool to retrieve a dataset by its UUID.

Get Dataset Ingress Logs

Tool to retrieve dataset ingress metrics over time.

List Feature Stores

Tool to list all feature stores.

Get Dependency Graph

Tool to retrieve the complete dependency graph for all resources on an account.

Get Market Opportunity Analyses

Tool to retrieve all market opportunity analyses from Faraday.

Get Outcome

Tool to retrieve an outcome by its ID.

List Outcomes

Tool to list all outcomes for the account.

Get Persona Set

Tool to retrieve a persona set by its UUID.

Get Persona Set Analysis Flow

Tool to retrieve the flow of persona sets over time, showing how individuals move between different personas.

List Persona Sets

Tool to list all persona sets.

Get Persona Set Analysis Dimensions

Tool to get various trait breakdown information about a persona set.

Get Place

Tool to retrieve a specific place by its UUID.

List Places

Tool to list all places in Faraday.

List Recommenders

Tool to list all recommenders.

Get Scope

Tool to retrieve detailed information about a Faraday scope by its UUID.

Get Scope Analysis

Tool to get analysis for a scope including outcomes and recommenders with probability distributions.

Get Scope Datasets

Tool to retrieve all datasets associated with a Faraday scope.

Get Scope Efficacy

Tool to retrieve efficacy metrics for a scope.

Get Scope Payload Cohorts

Tool to get payload cohorts for a specific scope.

Get Scope Payload Outcomes

Tool to retrieve payload outcomes for a specific scope.

Get Scope Payload Persona Sets

Tool to get payload persona sets for a specific scope.

Get Scope Payload Recommenders

Tool to retrieve payload recommenders for a specific scope.

Get Scope Population Exclusion Cohorts

Tool to get population exclusion cohorts for a scope.

Get Scope Population Cohorts

Tool to get population cohorts for a specific scope.

Get Scope Targets

Tool to get all targets for a specific scope.

Get Stream

Tool to retrieve a stream by its UUID or name.

List Streams

Tool to list all streams in your Faraday account.

Get Streams Analysis

Tool to get the count of stream events emitted over a time period.

Get Target

Tool to retrieve a specific target by its UUID from Faraday.

Get Target Analysis

Tool to retrieve a target's analysis including geographic distributions and trait breakdowns.

Get Trait

Tool to retrieve a specific trait by ID.

Get Trait Analysis Dimensions

Tool to retrieve the percentage of the US population that falls into each category of a trait.

Get Traits CSV

Tool to retrieve all user-defined and Faraday-provided traits in CSV format.

Get Upload

Tool to download a previously uploaded file from a Faraday dataset directory.

List Uploaded Files

Tool to retrieve the list of previously uploaded files in Faraday.

Get Usages

Tool to retrieve usage statistics for your Faraday account.

Get Webhook Endpoint

Tool to retrieve a webhook endpoint by its UUID.

List Webhook Endpoints

Tool to list all webhook endpoints configured for the account.

List Attributes

Tool to list all attributes in the feature store.

List Connections

Tool to list all connections configured in Faraday.

List Scopes

Tool to list all scopes.

List Targets

Tool to list all targets in your Faraday account.

Unarchive Cohort

Tool to unarchive a previously archived cohort.

Unarchive Dataset

Tool to unarchive a dataset in Faraday.

Unarchive Outcome

Tool to unarchive an outcome in Faraday.

Unarchive Persona Set

Tool to unarchive a previously archived persona set.

Unarchive Place

Tool to unarchive a previously archived place.

Unarchive Scope

Tool to unarchive a previously archived scope.

Unarchive Stream

Tool to unarchive a stream in Faraday.

Unarchive Trait

Tool to unarchive a trait.

Update Account

Tool to update an account's name or branding settings.

Update Cohort

Tool to update a cohort's configuration using JSON Merge Patch semantics.

Update Connection

Tool to update a Faraday connection's name or options.

Update Dataset

Tool to update a dataset configuration using JSON Merge Patch semantics.

Update Outcome

Tool to update an outcome's configuration using JSON Merge Patch semantics.

Update Persona Set

Tool to edit a persona set's configuration using JSON Merge Patch.

Update Place

Tool to update a place's name, addresses, or geojson geometry.

Update Scope

Tool to update a Faraday scope's configuration using JSON Merge Patch semantics.

Update Stream

Tool to update a stream's properties using JSON Merge Patch semantics.

Update Target

Tool to update a target's configuration in Faraday.

Update Trait

Tool to update a trait's properties using JSON Merge Patch semantics.

Update Webhook Endpoint

Tool to update a webhook endpoint's configuration.

FRAMEWORKS

How to build Faraday MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Faraday MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Faraday MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Faraday MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Faraday MCP with Claude Cowork

Codex logo

Codex

Use Faraday MCP with Codex

OpenClaw logo

OpenClaw

Use Faraday MCP with OpenClaw

Hermes logo

Hermes

Use Faraday MCP with Hermes

CLI logo

CLI

Use Faraday MCP with CLI

Google ADK logo

Google ADK

Use Faraday MCP with Google ADK

LangChain logo

LangChain

Use Faraday MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Faraday MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Faraday MCP with Mastra AI

CrewAI logo

CrewAI

Use Faraday MCP with CrewAI

FAQ

Frequently asked questions

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

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

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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
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.

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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.

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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.

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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.

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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.

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Co-Founder, Ingram Technologies