We're addressing a couple of key problems with using MCPs. First, many available MCP servers lack native or used-based authentications, creating security vulnerabilities and adding complexity during development.

Second, many MCP servers are personal projects, not designed for the reliability needed in production.

Connecting to these servers usually requires writing custom MCP client code for the MCP protocol itself, which is a barrier, especially if you already have function calling systems in place.

Klavis AI aims to address these issues. To simplify access, we offer an API to launch production-ready, hosted MCP servers quickly via our API. The API also provides built-in OAuth and multi-tenancy auth support for MCP servers.

We also want to remove the need for developers to write MCP client code. You can use our API to interact with any remote MCP servers directly from your existing backend infrastructure. For faster prototyping or direct user interaction, we also provide open-source client interfaces for Web, Slack, and Discord.

The MCP servers and clients code is open source because we want to contribute to the MCP community.

For a quick start in the hosted verions, log in to our website and generate an API key. Then start calling our APIs directly. You can find more details in our doc: https://docs.klavis.ai

For a quick start in the open source version, go to our github repository and check out the detailed readme on each MCP server and client.

A little note about myself: my background includes working on the function calling for Google Gemini. During that time, I saw firsthand the challenges teams face when trying to connect AI agents to external tools. I want to bring my insights and energy to accelerate MCP adoption.

This is an early release, and we’d appreciate feedback from the community. What are your worst pain points related to MCPs, either as a developer or a general user? What other MCP servers or features would be most valuable to you?

We'll be around in the comments. Thanks for reading!