# Klavis AI: hosted MCP integrations with user-level authentication

Canonical: https://mudpie.ai/companies/klavis-ai/
Breadcrumb: [Home](https://mudpie.ai/) / [Companies](https://mudpie.ai/companies/) / [Klavis AI: hosted MCP integrations with user-level authentication](https://mudpie.ai/companies/klavis-ai/)
Author: Ali Abouelatta (https://mudpie.ai/authors/ali-abouelatta/)
Published: 2026-09-19
Updated: 2026-09-19
Research type: Company profile
Method: Company and accelerator sources checked 2026-09-19. Product claims are attributed to their sources; this is research, not a hands-on product trial.

Klavis AI is building the integration layer between AI applications and external tools. Its public launch focuses on open-source, hosted MCP servers with OAuth, multi-tenant authentication and prebuilt clients so an agent product can connect to systems such as Jira without building every connector and auth flow itself.

## What it does

The [YC launch](https://www.ycombinator.com/launches/NSs-klavis-ai-open-source-mcp-integrations-for-ai-applications) says Klavis can launch hosted MCP servers through an API, connect remote servers from an existing backend and let users interact through web, Slack and Discord clients. It positions the service around enterprise-grade stability, remote access, OAuth and user-level authentication, while keeping servers and clients open source.

The buyer is an AI application team that needs many tool integrations but does not want to build MCP clients, multi-tenant auth and per-user OAuth from scratch. The YC profile now describes Klavis as supplying coding and agentic data for AI labs, so the product direction may be broader than the original MCP launch. The current homepage is a minimal sign-in surface and the checked pricing page does not publish plan details.

## Why I’d look closer

The advantage is removing the repeated integration work. A team can expose a Jira or other enterprise system through a hosted server while keeping its own application surface. Founder context fits the scale problem: Xiangkai Zeng worked on Google Gemini and co-authored the Gemini paper; Zihao Lin led recommendation and data-infrastructure work at Lyft and Nordstrom.

The tradeoff is the trust boundary. A hosted MCP server handles credentials, user identity, tool permissions and data returned to an agent. Open source helps inspection but does not remove the responsibility to configure scopes, isolate tenants and monitor tool calls.

## What I’d ask

Which servers are maintained, versioned and supported? How are OAuth tokens stored, scoped, refreshed and revoked? Can a customer inspect tool schemas, logs and outbound calls? What isolation exists between tenants? How does a team handle a connector breaking, a tool being over-permissioned or an upstream API changing?

## My editorial take

Shortlist Klavis if MCP integration breadth is blocking your agent product and you need user-level auth rather than a shared API key. Start with one low-risk tool, verify token scopes and log every call, then expand the server catalog. The value is production plumbing; the decision is whether you trust the plumbing with your users’ tools.

## Quick facts

| Field | Sourced detail |
| --- | --- |
| Product | Open-source/hosted MCP servers, clients, OAuth and multi-tenant auth |
| Buyer | AI application teams and frontier-agent builders |
| Example named | Hosted Jira MCP server with user authentication |
| Pricing | Not published in the checked pages |
| Main question | Can the integration layer keep tenant credentials and tool permissions contained? |

## Sources checked

| Source | Checked |
| --- | --- |
| [YC company profile](https://www.ycombinator.com/companies/klavis-ai) | 2026-09-19 |
| [Klavis AI YC launch](https://www.ycombinator.com/launches/NSs-klavis-ai-open-source-mcp-integrations-for-ai-applications) | 2026-09-19 |
| [Klavis AI homepage](https://www.klavis.ai/) | 2026-09-19 |

## Cohort context

Klavis AI is listed in Spring 2025. In our 2026-09-18 directory snapshot, 97 of 143 listed companies in that cohort have YC’s primary industry label B2B (67.8%). This is a current-directory comparison, not an original intake count or a performance ranking. [Nine-cohort dataset](https://mudpie.ai/research/yc-cohorts-2026-09-19.json).

## Public website snapshot

Observed 2026-09-19T16:15:43.252Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.

| Signal | Homepage observation |
| --- | --- |
| Product description metadata | Observed |
| Canonical link | Not observed in this response |
| H1 or H2 heading | Observed |
| Typed structured data | Observed |
| Docs/developer link | Observed |
| Pricing link | Observed |
| llms.txt link | Not observed in this response |
| Markdown alternate | Not observed in this response |

[Public observations](https://mudpie.ai/research/yc-homepage-links-2026-09-19.json) · [Collection method](https://mudpie.ai/research/yc-homepage-methods/README.md). Missing links here do not establish that a capability or file is absent elsewhere.


## Author disclosure

I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.