Klavis AI
ActiveDescription
MCP integration platform that lets AI agents use tools reliably at any scale, providing MCP servers, clients, and integration solutions for production agent workflows.
Key Features
- Strata intelligent connectors — optimize context windows for AI agents, smart tool call management
- 100+ prebuilt integrations — out-of-the-box MCP integrations with OAuth support
- MCP Sandbox — scalable MCP environments for LLM training and reinforcement learning
- Multi-SDK support — Python SDK, TypeScript SDK, and REST API available
- Self-hosting option — deploy via Docker or install Strata locally with pipx
- Cloud-hosted service — use directly via klavis.ai without building infrastructure
Use Cases
💡 Agent tool integration — let AI agents reliably call external tools like Gmail, Slack
💡 MCP protocol standardization — provide unified MCP interfaces for different tools
💡 LLM training environment setup — build scalable training environments with MCP Sandbox
💡 Large-scale agent deployment — manage multiple MCP server instances in production via SDK
💡 Rapid prototype validation — use cloud-hosted service to quickly validate agent tool call approaches
Categories
Quick Start
# Cloud-hosted (recommended)
# https://www.klavis.ai/docs/quickstart
# Self-host - Docker
docker pull ghcr.io/klavis-ai/github-mcp-server:latest
docker run -p 5000:5000 ghcr.io/klavis-ai/github-mcp-server:latest
# Self-host - Strata
pipx install strata-mcp
strata add --type stdio playwright npx @playwright/mcp@latest
# Python SDK
pip install klavis
from klavis import Klavis
from klavis.types import McpServerName
klavis = Klavis(api_key="your-key")
strata = klavis.mcp_server.create_strata_server(
user_id="user123",
servers=[McpServerName.GMAIL, McpServerName.SLACK]
)