How to connect Bigml to Claude Cowork

Cowork is Anthropic's AI agent for knowledge work. Think of it as Claude Code for everything else. It works autonomously with your computer, local files, and applications to accomplish complex tasks. This guide walks you through the easiest and most secure way to connect your Bigml account to Cowork via Composio Connect, enabling it to create a new BigML project for customer data, list all correlations available in your account, get details for a specific BigML project, and more such actions on your behalf without compromising your account security.

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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

Cowork is Anthropic's AI agent for knowledge work. Think of it as Claude Code for everything else. It works autonomously with your computer, local files, and applications to accomplish complex tasks.

This guide walks you through the easiest and most secure way to connect your Bigml account to Cowork via Composio Connect, enabling it to create a new BigML project for customer data, list all correlations available in your account, get details for a specific BigML project, and more such actions on your behalf without compromising your account security.

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Connecting Bigml to Claude Cowork

1. Open Customize

In Claude Desktop, click Customize in the left sidebar, then select Connectors and click the + icon at the top.

Claude Desktop connectors screen with Add custom connector selected

2. Add the Composio MCP server

Click Add custom connector and paste in the Composio MCP server URL:

bash
https://connect.composio.dev/mcp
Add custom connector dialog with Composio MCP server URL

3. Authorize in your browser

Click Connect. You'll be redirected to a browser window where you can authorize Composio to continue.

Composio authorization screen for Claude Cowork

4. Connect your Bigml account

Back in Cowork, ask the agent to connect to Bigml or give it any Bigml-related task.

For example, ask Cowork to:

  • "Create a new BigML project for customer data"
  • "List all correlations available in your account"
  • "Get details for a specific BigML project"

It will prompt you to authenticate and authorize access.

That's it. Composio's tools are now available in Cowork, and your Bigml account is ready to use.

What is Claude Cowork?

Claude Cowork is Anthropic's agent for general knowledge work. It can use your computer, files, and connected applications to complete longer-running tasks across your work tools.

With Composio Connect, Cowork can securely access apps like Bigml through MCP without you sharing account credentials directly with the agent.

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.
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.

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 Cowork 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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