What are the prerequisites to use this integration?
You need access to the Planning Center API, a Python environment, an MCP client (such as Claude Desktop), and API keys for authentication.
@jake-ccnh
基本情報
Planning Center Online MCP Server
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": {
"pco-mcp": {
"command": "uv",
"args": [
"pip",
"install",
"-r",
"requirements.txt"
]
}
}
}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。
This integration connects the Planning Center Online (PCO) API with an MCP server, enabling a Large Language Model (LLM) to answer natural language queries and retrieve data from Planning Center. It is designed for users who want to interact with their Planning Center data conversationally.
Clone the repository, install dependencies with uv pip install -r requirements.txt, and configure PCO_SECRET_KEY and PCO_APPLICATION_ID as environment variables. Test the server using fastmcp dev services.py, then add the provided MCP server configuration to your MCP client (e.g., Claude Desktop). Send natural language queries to the server, which processes them and interacts with the PCO API to return structured responses or perform actions.
You need access to the Planning Center API, a Python environment, an MCP client (such as Claude Desktop), and API keys for authentication.
Set the environment variables `PCO_SECRET_KEY` for your Planning Center API key and `PCO_APPLICATION_ID` for the URL of the MCP server.
The README does not specify the underlying transport; it references FASTMCP and demonstrates usage via an MCP client configuration using the `fastmcp run` command.
The project states that future work intends to continue development on other areas of Planning Center, implying current scope may be limited to services.
You need Python, the packages listed in `requirements.txt` (installed via `uv pip install`), and access to the Planning Center Online API.
ArduPilotドローンをAIエージェントから操作するMCPサーバーです。
emergency-medicare-planner-mcp-server
AI-powered n8n workflow automation through natural language. MCP server enabling Claude AI & Cursor IDE to create, manage, and monitor workflows via Model Context Protocol. Multi-instance support, 17 tools, comprehensive docs. Build workflows conversationally without manual JSON
MCP server that gives Claude persistent project memory — roadmap, session history, and codebase context. Type continue and Claude picks up exactly where you left off
This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.
コメント