head to head · open source
vllm vs mcp-server-elasticsearch
vllm has 92,055 GitHub stars, 22,349 forks, 7,953 open issues and last shipped today. mcp-server-elasticsearch has 717 stars, 153 forks, 23 open issues and last shipped today. vllm leads on adoption by 12,739% (92,055 vs 717 stars). vllm is written in Python under Apache-2.0; mcp-server-elasticsearch is written in Rust under Apache-2.0. vllm has attracted 24% as many forks as stars, mcp-server-elasticsearch 21%. vllm 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
| vllm | mcp-server-elasticsearch | |
|---|---|---|
| GitHub stars | ★ 92K | ★ 717 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Rust |
| Last push | 2026-09-18 | 2026-09-18 |
| Forks | ⑂ 22K | ⑂ 153 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick vllm if
- You weight community size — 92K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick mcp-server-elasticsearch if
- You want the mcp-server-elasticsearch feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and mcp-server-elasticsearch fits your workflow better
About vllm
vLLM is a high throughput, memory efficient Python library for LLM inference and serving, built for ML engineers and platform teams who need to run open weight models on their own hardware at production scale.
About mcp-server-elasticsearch
Elasticsearch MCP Server [!CAUTION] This MCP server is deprecated and will only receive critical security updates going forward. It has been superseded by the Elastic Agent Builder MCP endpoint, which is available in Elastic 9.2.0+ and Elasticsearch Serverless projects. Use the Elasticsearch MCP Server for AI Agents The Elasticsearch MCP Server connects your AI agents to Elasticsearch data using the Model Context Protocol (MCP). It enables natural language interactions with your Elasticsearch indices, allowing agents to query, analyze, and retrieve data without custom APIs. Follow these steps to deploy and config…
read the full mcp-server-elasticsearch overview →
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Frequently asked questions
Is vllm or mcp-server-elasticsearch more popular?
vllm has 92,055 GitHub stars and mcp-server-elasticsearch has 717. vllm has the larger community by that measure.
Are vllm and mcp-server-elasticsearch free?
Both are open source. vllm is licensed under Apache-2.0 and mcp-server-elasticsearch under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and mcp-server-elasticsearch?
vllm is written in Python and mcp-server-elasticsearch in Rust. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, vllm or mcp-server-elasticsearch?
Choose vllm if you want the larger community (92,055 stars) or its Apache-2.0 licence terms. Choose mcp-server-elasticsearch if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.