head to head · open source
Weaviate vs mcp-toolbox
Weaviate has 16,934 GitHub stars, 1,433 forks, 738 open issues and last shipped yesterday. mcp-toolbox has 16,792 stars, 1,787 forks, 292 open issues and last shipped yesterday. Weaviate leads on adoption by 1% (16,934 vs 16,792 stars). Weaviate is written in Go under a custom or non-standard licence; mcp-toolbox is written in Go under Apache-2.0. Weaviate has attracted 8% as many forks as stars, mcp-toolbox 11%. Weaviate was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Weaviate | mcp-toolbox | |
|---|---|---|
| GitHub stars | ★ 17K | ★ 17K |
| License | Custom / other | Apache-2.0 |
| Written in | Go | Go |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 1.4K | ⑂ 1.8K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Weaviate if
- You weight community size — 17K stars and counting
- You want the Custom / other license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick mcp-toolbox if
- You want the mcp-toolbox feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Go
- You evaluated both and mcp-toolbox fits your workflow better
About Weaviate
Weaviate Weaviate is an open source, cloud native vector database that stores both objects and vectors, enabling semantic search at scale. It combines vector similarity search with keyword filtering, retrieval augmented generation (RAG), and reranking in a single query interface. Common use cases include RAG systems, semantic and image search, recommendation engines, chatbots, and content classification. Weaviate supports two approaches to store vectors: automatic vectorization at import using integrated models (OpenAI, Cohere, HuggingFace, and others) or direct import of pre computed vector embeddings…
read the full Weaviate overview →
About mcp-toolbox
MCP Toolbox for Databases MCP Toolbox for Databases is an open source Model Context Protocol (MCP) server that connects your AI agents, IDEs, and applications directly to your enterprise databases. It serves a dual purpose : 1. Ready to use MCP Server (Build Time): Instantly connect Gemini CLI, Google Antigravity, Claude Code, Codex, or other MCP clients to your databases using our prebuilt generic tools . Talk to your data, explore schemas, and generate code without writing boilerplate. 2. Custom Tools Framework (Run Time): A robust framework to build specialized, highly secure AI tools for your production…
read the full mcp-toolbox overview →
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Frequently asked questions
Is Weaviate or mcp-toolbox more popular?
Weaviate has 16,934 GitHub stars and mcp-toolbox has 16,792. Weaviate has the larger community by that measure.
Are Weaviate and mcp-toolbox free?
Both are open source. Weaviate has no licence declared in this registry, and mcp-toolbox is licensed under Apache-2.0. Both are free to self-host.
What is the difference between Weaviate and mcp-toolbox?
Weaviate is written in Go and mcp-toolbox in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Weaviate or mcp-toolbox?
Choose Weaviate if you want the larger community (16,934 stars) or its Custom / other licence terms. Choose mcp-toolbox if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.