by open-webui · MCP Server · ★ 865
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🌟 OpenAPI Tool Servers This repository provides reference OpenAPI Tool Server implementations making it easy and secure for developers to integrate external tooling and data sources into LLM agents and workflows. Designed for maximum ease of use and minimal learning curve, these implementations utilize the widely adopted and battle-tested OpenAPI specification as the standard protocol. By leveraging OpenAPI, we eliminate the need for a proprietary or unfamiliar communication protocol, ensuring you can quickly and confidently build or integrate servers. This means less time spent figuring out custom interfaces and more time building powerful tools that enhance your AI applications. ☝️ Why OpenAPI? Established Standard: OpenAPI is a widely used, production-proven API standard backed by thousands of tools, companies, and communities. No Reinventing the Wheel: No additional documentation or proprietary spec confusion. If you build REST APIs or use OpenAPI today, you're already set. Easy Integration & Hosting: Deploy your tool servers externally or locally without vendor lock-in or complex configurations.
| Stars | 865 |
| Forks | 159 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.7662326816487/100 |
| Open Issues | 2 |
| Last Updated | 2025-09-25 |
| Created | 2025-03-27 |
| Platforms | mcp, python |
| Est. Tokens | ~8k |
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openapi-servers is OpenAPI Tool Servers. It is categorized as a MCP Server with 865 GitHub stars.
openapi-servers is primarily written in Python. It covers topics such as ai, mcp, openapi.
You can find installation instructions and usage details in the openapi-servers GitHub repository at github.com/open-webui/openapi-servers. The project has 865 stars and 159 forks, indicating an active community.
openapi-servers is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openapi-servers on Agent Skills Hub include flock, reverse-api-engineer, mcpcan. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.