MaxKB vs core
AI agent platforms compared
MaxKB and core are Python projects for building conversational AI agents. MaxKB focuses on knowledge-grounded assistants, workflows, and business-system integration, while core is a framework and service for exploring and extending agents through a local UI, REST API, and plugins.
MaxKB: Build and Run Enterprise AI Agents
MaxKB is a self-hostable platform for building AI agents that use company knowledge, workflows, and external tools. It suits teams that want to add model-backed question answering to internal or customer-facing systems.
core: Build and Extend AI Agents
Cheshire Cat AI is a Python framework and microservice for building conversational AI agents. It is aimed at learning, research, and publishing agents, with a local UI and REST API for exploring and extending them.
| MaxKB | core | |
|---|---|---|
| Language | Python | Python |
| License | GPL-3.0 | GPL-3.0 |
| Stars | 22.9k | 3.1k |
| Forks | 3.2k | 411 |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- MaxKB provides document and online-content ingestion for knowledge-based question answering; core is described as a conversational agent framework and service.
- MaxKB emphasizes workflows, a function library, and connecting agents to business systems; core emphasizes plugins, a browser UI, a REST API, and an API playground.
- MaxKB lists support for public and private model providers and text, image, audio, and video inputs and outputs; core's listed areas include function calling, vector search, and MCP.
- MaxKB documents PostgreSQL with pgvector as its database and vector store; core offers local installation through the `cheshire-cat-ai` package.
- Both use Python and GPL-3.0. MaxKB has 22.9k stars and 3.2k forks, while core has 3.1k stars and 411 forks.
- Core's README describes version 2 as an unstable alpha with breaking changes and advises against production use; MaxKB's considerations focus on operating and securing a self-hosted deployment.
Choose MaxKB if you…
- need a knowledge base built from documents or online content for grounded answers.
- want to orchestrate tasks with workflows and connect agents to business systems.
- need support for multiple model providers or multimodal input and output.
Choose core if you…
- want a Python service with a local browser UI, REST API, and API playground.
- want to learn about or prototype conversational agents and extend them with plugins.
- are exploring function calling, vector search, or MCP integrations and can work with an unstable alpha.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.