ChipsAI MCP Server
Operate ChipsAI chatbots, conversations, and models from your IDE agent via MCP instead of switching to a separate admin UI.
Overview
ChipsAI MCP is a Build-phase MCP server that lets agents manage ChipsAI chatbots, conversations, and AI models over stdio.
What is this MCP server?
- MCP control plane for ChipsAI chatbots, conversations, and AI models
- PyPI stdio package chipsai-mcp v1.0.1
- Account auth via CHIPSAI_EMAIL and CHIPSAI_PASSWORD environment variables
- Keeps bot and model administration inside Claude Code–style workflows
- From fgasparetto/chipsai-mcp on GitHub
- Server version 1.0.1
- PyPI identifier chipsai-mcp with stdio transport
- 2 required credential environment variables
What problem does it solve?
Switching between your editor and ChipsAI’s web console breaks flow when you need frequent bot and model tweaks during development.
Who is it for?
Builders already on ChipsAI who want agent-driven administration of bots and models from Claude Code or Cursor.
Skip if: Developers without a ChipsAI account or anyone building chat purely on raw OpenAI/Anthropic APIs with no ChipsAI platform.
What do I get? / Deliverables
After registration, your agent can list and adjust ChipsAI bots, chats, and models from the same session where you edit application code.
- Agent-callable management of ChipsAI bots, conversations, and models
- Fewer context switches to the ChipsAI web UI during implementation
- Repeatable bot configuration steps driven from the repo session
Recommended MCP Servers
Journey fit
ChipsAI management is part of building and running your AI product surface, which catalogues under Build agent-tooling for MCP control planes. Agent-tooling is the right shelf for MCP servers that configure bots, models, and conversational assets your product exposes to users.
How it compares
Hosted-platform admin MCP, not a local RAG skill or a generic prompt library.
Common Questions / FAQ
Who is ChipsAI MCP for?
Indie builders and small teams using the ChipsAI platform who want MCP-driven control of chatbots, conversations, and models from their coding agent.
When should I use ChipsAI MCP?
Use it during Build when you are configuring bots, swapping models, or reviewing conversation setup while implementing your AI feature.
How do I add ChipsAI MCP to my agent?
Install the PyPI package chipsai-mcp, configure stdio MCP in your client, and set required CHIPSAI_EMAIL and CHIPSAI_PASSWORD in the environment.