What are the system requirements for Kylas?
Python 3.10+ and a Kylas account with an API key.
@kylastech
基本信息
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使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"kylas-crm": {
"command": "PASTE_THE_PATH_FROM_which_kylas_crm_mcp",
"env": {
"KYLAS_API_KEY": "THEIR_KYLAS_API_KEY"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Kylas is a Model Context Protocol (MCP) server for Kylas CRM lead operations. It allows MCP clients like Cursor or Claude Desktop to create leads, search and filter leads, and look up users, products, and pipelines.
Install with pip install -e . or from PyPI after publication. Set the KYLAS_API_KEY environment variable (required) and optionally KYLAS_BASE_URL. Run the server via python -m kylas_crm_mcp or use the provided Docker image. MCP clients communicate over stdio. Available commands include create_lead, search_leads, lookup_users, lookup_products, lookup_pipelines, get_pipeline_stages, and search_idle_leads.
Python 3.10+ and a Kylas account with an API key.
Set the `KYLAS_API_KEY` environment variable. Optionally set `KYLAS_BASE_URL` (default: https://api.kylas.io/v1). Configuration can also be placed in a `.env` file.
Kylas uses stdio transport, the default for MCP. Clients start the server process and communicate via stdin/stdout.
Yes. Build the image with `docker build -t kylas-crm-mcp .` and run it, passing the API key via the `-e` flag: `docker run -e KYLAS_API_KEY=your_key -i kylas-crm-mcp`.
Publish the package to PyPI, then use the `mcp-publisher` tool (login via GitHub and run `mcp-publisher publish`). Full instructions are in PUBLISHING.md.

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