What are the system requirements for Kylas?
Python 3.10+ and a Kylas account with an API key.
@kylastech
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"kylas-crm": {
"command": "PASTE_THE_PATH_FROM_which_kylas_crm_mcp",
"env": {
"KYLAS_API_KEY": "THEIR_KYLAS_API_KEY"
}
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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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