XiaoheiheMcpServer links MCP assistants to the Xiaoheihe platform
XiaoheiheMcpServer by Wsmxd is an MCP server that connects AI assistants to the Xiaoheihe gaming platform for content access and publishing. It exposes Xiaoheihe data to AI models, enabling research, summarization, and automated content workflows across community posts and news feeds. Key tools include content publishing, data retrieval, game database queries, and Playwright-based browser automation for authentication. The project targets Xiaoheihe community members, AI power users, and developers seeking programmatic platform integration and automation for content management and analysis.
What tasks can you actually use it for?
The server turns Xiaoheihe social and content endpoints into callable MCP tools, so AI clients can perform research, summarization, and draft generation tied to platform data. It supports publishing formats including short posts and long-form articles, and it can upload local images automatically during publication. For content creators this means the model can prepare community-facing drafts and summaries using explicit post fields rather than scraping raw pages.
How reliable are its publish and retrieval actions?
The server exposes detailed post fields, including titles, body text, and comments, and it provides access to real-time news feeds, so generated summaries and analyses use concrete inputs. Browser automation runs under Playwright to handle complex interactions and authentication, and that automation identifies and uploads images and attachments during publication. Because tools return structured fields, AI outputs can reference explicit content elements instead of relying on raw HTML extraction.
What inputs and setup are required?
The server requires a Node.js environment and a modern Chromium-based browser for automation. Installation offers an HTTP package or a repository clone with provided setup scripts. Publishing needs a logged-in Xiaoheihe session that the server manages via QR code or cookies. The server connects to MCP-compliant hosts and runs on Windows, macOS, and Linux. Example compatible hosts include Claude Desktop.
- Node.js runtime
- Chromium-based browser for Playwright
- Setup scripts (setup.ps1 or setup.sh)
Is it easy to integrate with existing AI workflows?
The server supports both Stdio and HTTP transports, enabling flexible connections to MCP hosts without bespoke adapters. Because it implements the Model Context Protocol, AI clients that speak MCP can call tools directly, reducing integration code. The project targets developers and AI power users who can embed calls into agent stacks and content pipelines, and it runs across Windows, macOS, and Linux for multi-platform deployment.
Practical judgment and next steps
The server is a pragmatic bridge for technically capable integrators and community-focused AI users; the developer maintains it with regular updates and visible community interest. Adopt a dedicated testing account and keep human review in the deployment loop to catch platform-specific moderation and tone issues, and include compliance checks before wide publication. Use it as an assistive layer, and validate outputs before publishing.
