広告掲載
MCP.so
ログイン
K

Kylas MCP Server

@kylastech

リポジトリ

基本情報

カテゴリ

データと分析

トランスポート

stdio

作者

kylastech

投稿者

Akshay Gunshetti

Kylas MCP Server について

概要はまだありません

Kylas MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "kylas-crm": {
      "command": "PASTE_THE_PATH_FROM_which_kylas_crm_mcp",
      "env": {
        "KYLAS_API_KEY": "THEIR_KYLAS_API_KEY"
      }
    }
  }
}

Kylas MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Kylas?

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.

How to use Kylas?

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.

Key features of Kylas

  • Create leads with dynamic fields from user context
  • Search and filter leads by multiple criteria
  • Resolve user names to IDs for ownership fields
  • Resolve product names and pipeline stages
  • Find leads idle for N days

Use cases of Kylas

  • Create new leads in Kylas CRM from an AI assistant
  • Search for leads based on custom filters and criteria
  • Automatically map user, product, and pipeline names to internal IDs
  • Identify leads with no recent activity for follow-up

よくある質問

1

What are the system requirements for Kylas?

Python 3.10+ and a Kylas account with an API key.

2

How do I configure Kylas?

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.

3

What transport does Kylas use?

Kylas uses stdio transport, the default for MCP. Clients start the server process and communicate via stdin/stdout.

4

Can Kylas be run with Docker?

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`.

5

How do I publish Kylas to the MCP Marketplace?

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.

コメント

「データと分析」の他のコンテンツ

FastSocial Instagram Data

FastSocialCo

Read-only public Instagram data as JSON: profiles, posts, reels, stories, comments and daily top-accounts charts. Free plan with 50 credits a month.

Databar.ai

databar-ai

Databar.ai enables access to 100+ third party data providers, waterfall enrichments, and company signals via a single MCP server. It offers two additional products - Flows, which enable agents to build re-usable enrichme

P

ProLevelMax

ProLevelMax

The real-time social data source for AI. Public posts, comments, profiles, search and trends from TikTok, Instagram, YouTube, Reddit, X, Xiaohongshu, Douyin, Weibo, Amazon reviews, Google Maps and more: 157 platforms in

Jitsu

Jitsu

Jitsu is an open-source Customer Data Platform — an MIT-licensed alternative to Segment. This MCP server gives your AI assistant direct control over a Jitsu workspace, so you can run and debug data pipelines in conversat

AskRentAI

AskRentAI

Ask your Rent Manager property portfolio anything, from the AI you already use. AskRentAI is a hosted, read-only MCP server for Rent Manager, the property management platform used across a large share of US rental housi

広告掲載