How to integrate Bigml MCP with Claude Agent SDK

This guide walks you through connecting Bigml to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Bigml agent that can create a new bigml project for customer data, list all correlations available in your account, get details for a specific bigml project through natural language commands. This guide will help you understand how to give your Claude Agent SDK agent real control over a Bigml account through Composio's Bigml MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient.

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Introduction

This guide walks you through connecting Bigml to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Bigml agent that can create a new bigml project for customer data, list all correlations available in your account, get details for a specific bigml project through natural language commands.

This guide will help you understand how to give your Claude Agent SDK agent real control over a Bigml account through Composio's Bigml MCP server.

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

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TL;DR

Here's what you'll learn:
  • Get and set up your Claude/Anthropic and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Bigml
  • Configure an AI agent that can use Bigml as a tool
  • Run a live chat session where you can ask the agent to perform Bigml operations

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

What is the Bigml MCP server, and what's possible with it?

The Bigml MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bigml account. It provides structured and secure access to your machine learning environment, so your agent can perform actions like creating projects, managing data connectors, inspecting resources, and analyzing correlations on your behalf.

  • Project creation and organization: Easily direct your agent to create new projects to group related BigML resources for streamlined workflows.
  • External data connector management: Have your agent set up and retrieve external connectors to bring in data from external sources and databases.
  • Resource inspection and retrieval: Let your agent fetch detailed metadata about projects or connectors, helping you monitor and audit your ML assets.
  • Automated project cleanup: Instruct your agent to delete obsolete or unused projects, ensuring your workspace stays organized and efficient.
  • Correlation browsing and analysis: Ask your agent to list and paginate correlation resources, uncovering relationships among your datasets for deeper insights.

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A Bigml account
  • Some knowledge of Python
2

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @anthropic-ai/claude-agent-sdk @composio/core dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • @composio/core provides Composio integration for Anthropic
  • @anthropic-ai/claude-agent-sdk is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude
5

Import dependencies

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The dotenv.config() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with Bigml functionality
6

Create a Composio instance and Tool Router session

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });

  // Create Tool Router session for Bigml
  const session = await composio.create(USER_ID, {
    toolkits: ['bigml'],
  });
  const mcpUrl = session?.mcp.url;
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for Bigml
  • The returned url is the MCP server URL that your agent will use
7

Configure Claude Agent with MCP

const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to Bigml tools via Composio.',
  maxTurns: 10,
};
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permissionMode: 'bypassPermissions' allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to Bigml
  • maxTurns: 10 limits the conversation length to prevent excessive API usage
8

Create client and start chat loop

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
What's happening:
  • The readline interface is created to handle user input and output
  • The query function is used to send the user's input to the agent
  • The chat loop continues until the user types 'exit' or 'quit'
9

Run the application

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
What's happening:
  • The chat function is the entry point for the application
  • The try-catch block is used to handle any errors that occur

Complete Code

Here's the complete code to get you started with Bigml and Claude Agent SDK:

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['bigml']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to Bigml tools via Composio.',
    maxTurns: 10,
  };

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
  });

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Bigml through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

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

Create External Connector

Tool to create a new external connector for data sources.

Create Project

Tool to create a new project.

Delete Project

Tool to delete an existing project.

Get Configuration

Retrieves complete details of a BigML configuration by its ID to get stored parameters.

Get External Connector

Retrieves complete details of a BigML external connector by its ID.

Get Project

Tool to retrieve details of a project by ID.

Get Source

Retrieves complete details of a BigML source by its ID.

List Anomaly Detectors

Tool to list anomaly detector resources in your account.

List Anomaly Scores

Tool to list anomaly score resources.

List Associations

Tool to list association resources.

List Association Sets

Tool to list association set resources in your account.

List Batch Anomaly Scores

Tool to list batch anomaly score resources.

List Batch Centroids

Tool to list all batch centroid resources in your account with support for filtering, ordering, and pagination.

List Batch Predictions

Tool to list batch prediction resources.

List Batch Projections

Tool to list batch projection resources with support for filtering, ordering, and pagination.

List Batch Topic Distributions

Tool to list batch topic distribution resources.

List Centroids

Tool to list centroid resources.

List Clusters

Tool to list cluster resources with support for filtering, ordering, and pagination.

List Composites

Tool to list composite source resources.

List Configurations

Tool to list all configuration resources in your account.

List Correlations

Tool to list correlation resources.

List Datasets

Tool to list dataset resources.

List Deepnets

Tool to list deep neural network resources.

List Ensembles

Tool to list ensemble resources with filtering, ordering, and pagination support.

List Evaluations

Tool to list evaluation resources.

List Executions

Tool to list execution resources.

List Forecasts

Tool to list forecast resources.

List Fusions

Tool to list fusion resources.

List Libraries

Tool to list WhizzML library resources.

List Linear Regressions

Tool to list linear regression resources.

List Logistic Regressions

Tool to list logistic regression resources.

List Models

Tool to list model resources.

List OptiMLs

Tool to list OptiML resources in your account.

List PCAs

Tool to list PCA resources.

List Predictions

Tool to list prediction resources.

List Projections

Tool to list projection resources with support for filtering, ordering, and pagination.

List Projects

Tool to list all project resources in your account with support for filtering, ordering, and pagination.

List Samples

Tool to list sample resources.

List Scripts

Tool to list WhizzML script resources.

List Sources

Tool to list source resources in your account.

List Statistical Tests

Tool to list statistical test resources.

List Time Series

Tool to list time series resources.

List Topic Distributions

Tool to list topic distribution resources.

List Topic Models

Tool to list topic model resources.

Update Source

Tool to update a source's name, description, tags, or parsing configuration.

FRAMEWORKS

How to build Bigml MCP Agent with another framework

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OpenAI Agents SDK

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Claude Code

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Claude Cowork logo

Claude Cowork

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Codex logo

Codex

Use Bigml MCP with Codex

OpenClaw logo

OpenClaw

Use Bigml MCP with OpenClaw

Hermes logo

Hermes

Use Bigml MCP with Hermes

CLI logo

CLI

Use Bigml MCP with CLI

Google ADK logo

Google ADK

Use Bigml MCP with Google ADK

LangChain logo

LangChain

Use Bigml MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Bigml MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Bigml MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Bigml MCP with LlamaIndex

CrewAI logo

CrewAI

Use Bigml MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Claude Agent SDK 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 Bigml tools.

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

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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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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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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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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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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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