What is the difference between this server and the full CData MCP Server for Asana?
This server is read-only. The full CData MCP Server for Asana supports read, write, update, delete, and actions with a simpler setup.
@CDataSoftware
基本信息
This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Asana (beta): https://www.cdata.com/download/download.aspx?sku=UJZK-V&type=beta
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"{classname_dash}": {
"command": "PATH\\TO\\java.exe",
"args": [
"-jar",
"PATH\\TO\\CDataMCP-jar-with-dependencies.jar",
"PATH\\TO\\asana.prp"
]
}
}
}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。
Asana MCP Server by CData is a read-only MCP server that allows LLMs like Claude Desktop to query live Asana data via natural language. It uses the CData JDBC Driver for Asana to model Asana data as relational SQL tables, exposed through a simple MCP interface.
Clone the repository, build with Maven, install and license the CData JDBC Driver for Asana, create a .prp file with the JDBC connection string, then configure your AI client (e.g., Claude Desktop) by adding the server to claude_desktop_config.json with the path to the JAR and .prp file. The server runs locally via stdio.
This server is read-only. The full CData MCP Server for Asana supports read, write, update, delete, and actions with a simpler setup.
You need Java, Maven, and a licensed copy of the CData JDBC Driver for Asana installed on the same machine as the MCP client.
The server queries live Asana data via the JDBC Driver. Data is not stored or cached locally by the server.
The server uses stdio transport, so it must run on the same machine as the AI client.
Authentication uses OAuth via the JDBC Driver. During setup, you authenticate in your browser, and the driver refreshes tokens automatically.
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

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