mcpField
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Kylas

Kylas

Local
github.com/kylastechData & Analytics12Updated 37w ago
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About Kylas

Kylas is an MCP server for lead-focused operations in Kylas CRM. It supports creating and filtering leads, and resolving related users, products, and pipeline details for MCP clients.

Key features

  1. 01Get lead field instructions
  2. 02Create leads with dynamic fields
  3. 03Search and filter leads
  4. 04Resolve user and product IDs
  5. 05Look up pipelines and stages
  6. 06Find leads without recent activity

Use cases

  1. 01Create a CRM lead from context
  2. 02Find leads matching criteria
  3. 03Resolve names to CRM IDs
  4. 04Identify leads idle for a set period

MCP support

The server exposes Kylas CRM lead operations and lookups to MCP clients, using stdio transport. It requires a Kylas API key.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "kylas-crm": {
      "command": "uvx",
      "args": [
        "kylas-crm-mcp-server"
      ],
      "env": {
        "KYLAS_API_KEY": "<KYLAS_API_KEY>",
        "KYLAS_BASE_URL": "<KYLAS_BASE_URL>"
      }
    }
  }
}
Run commanduvx kylas-crm-mcp-server
Environment variables to set
KYLAS_API_KEYSecretYour Kylas API key (required)
KYLAS_BASE_URLKylas API base URL (optional, default: https://api.kylas.io/v1)

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypikylas-crm-mcp-server1.0.4

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Kylas CRM MCP Server (Lead Only)

Model Context Protocol server for Kylas CRM lead operations. Use it from Cursor, Claude Desktop, or any MCP client to create leads, search and filter leads, and look up users, products, and pipelines.

Features

  • get_lead_field_instructions – Get lead schema (standard + custom fields, picklist IDs)
  • create_lead – Create a lead with dynamic fields from user context
  • search_leads – Search/filter leads by multiple criteria
  • lookup_users – Resolve user names to IDs (for owner, created by, etc.)
  • lookup_products – Resolve product names to IDs
  • lookup_pipelines / get_pipeline_stages – Resolve pipeline and stage for open/closed/won leads
  • search_idle_leads – Find leads with no activity for N days

Requirements

  • Python 3.10+
  • Kylas account and API key

Installation

pip install -e .
# or from PyPI (after publish): pip install kylas-crm-mcp-server

Configuration

Set environment variables (or use a .env file):

VariableRequiredDescription
KYLAS_API_KEYYesYour Kylas API key
KYLAS_BASE_URLNoAPI base URL (default: https://api.kylas.io/v1)

Running the server

The server uses stdio transport (default for MCP). Run:

python -m kylas_crm_mcp
# or: python main.py  (when developing from repo root)

MCP clients (e.g. Cursor) typically start this process and communicate via stdin/stdout.

Docker

docker build -t kylas-crm-mcp .
docker run -e KYLAS_API_KEY=your_key -i kylas-crm-mcp

Development

pip install -e ".[dev]"
pytest

Publishing to the MCP Marketplace

To publish this server to the official MCP Registry (so it appears in Cursor and other MCP clients):

  1. Publish the package to PyPI (the registry verifies ownership via your README).
  2. Install mcp-publisher and run mcp-publisher login github, then mcp-publisher publish.

See PUBLISHING.md for the full step-by-step guide.

License

See repository for license information.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.