What MCP tools does the server provide?
The server provides four tools: inputPrompt (mandatory), addFile (optional), intermediateResults (optional), and processingResult (mandatory). They correspond directly to COMPLiQ API endpoints.
@rosedael
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"compliq": {
"command": "npx",
"args": [
"mcp-remote",
"https://compliq-mcp-server.<your-account>.workers.dev/sse"
]
}
}
}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。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
COMPLiQ MCP Server on Cloudflare is a Model Context Protocol (MCP) server deployed on Cloudflare Workers that enables AI assistants to interact with the COMPLiQ platform. It provides MCP tools for submitting prompts, attaching files, and sending intermediate and final results to COMPLiQ, a platform that logs AI interactions.
Clone the repository, configure your COMPLIQ_API_KEY using npx wrangler secret put COMPLIQ_API_KEY, then deploy with npm run deploy. Once deployed, connect an MCP client (e.g., Claude Desktop) by adding a configuration with the command npx mcp-remote and the server URL https://compliq-mcp-server.<your-account>.workers.dev/sse.
inputPrompt tool.addFile tool.intermediateResults.processingResult.The server provides four tools: inputPrompt (mandatory), addFile (optional), intermediateResults (optional), and processingResult (mandatory). They correspond directly to COMPLiQ API endpoints.
Set your COMPLiQ API key as a Cloudflare Worker secret using `npx wrangler secret put COMPLIQ_API_KEY` before deployment. The key is required for all API calls.
The server uses four endpoints: `https://ai-stage-be.compliq.io/v1/actions/task-input`, `/file-input`, `/resources-used`, and `/output`.
After deployment, configure your MCP client with the command `npx mcp-remote` and the argument `https://compliq-mcp-server.<your-account>.workers.dev/sse`. The server communicates via SSE transport.
`inputPrompt` and `processingResult` are mandatory; `addFile` and `intermediateResults` are optional. You must always start with inputPrompt and end with processingResult.
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