TeamSpark AI Workbench

What is TeamSpark AI Workbench?

TeamSpark AI Workbench is a local development environment for AI and machine learning projects, offering both a graphical interface and a command-line interface on Mac, Linux, and Windows.

How to use TeamSpark AI Workbench?

On installed releases, launch the CLI with a provided shell script: on MacOS run tspark.sh or create a symlink; on Linux run teamspark-workbench --cli or use tspark.sh. You must run the CLI in a directory containing a workspace or pass one via --workspace; use --create to initialize a new workspace.

Key features of TeamSpark AI Workbench

• Supports many LLM providers (Claude, ChatGPT, Gemini, Bedrock, Ollama)
• References (memory) and Rules (prompt guidance) for context control
• Tool usage via MCP with thousands of available tools
• Internal tools let models update their own references and rules
• Chat sessions with selectable models and configurable context

Use cases of TeamSpark AI Workbench

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FAQ from TeamSpark AI Workbench

What license does TeamSpark AI Workbench use?

The repository is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), which prohibits modifications and commercial use without permission.

Can I use TeamSpark AI Workbench for commercial purposes?

No, not without explicit permission. Contact support@teamspark.ai for commercial licensing.

What platforms does TeamSpark AI Workbench support?

It runs on MacOS, Linux, and Windows as a local client application.

Does TeamSpark AI Workbench support MCP tools?

Yes, it supports tool usage via the Model Context Protocol (MCP), making thousands of tools available to models.

Which LLM providers are supported?

TeamSpark AI Workbench supports Anthropic/Claude, OpenAI/ChatGPT, Google/Gemini, AWS Bedrock, and Ollama.