Train, explain, optimise and deploy transparent glass-box ML models via workflow tools.
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io.github.xplainable/xplainable-mcp-server is an MCP server that train, explain, optimise and deploy transparent glass-box ML models via workflow tools. Its tool list has not been published yet over http, requires no API key, and scores 42/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"xplainable": {
"env": {
"XPLAINABLE_API_KEY": "your-api-key-here"
},
"args": [
"--from",
"git+https://github.com/xplainable/xplainable-mcp-server.git",
"xplainable-mcp"
],
"command": "uvx"
}
}
}Are you the author?
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A Model Context Protocol server for the Xplainable platform. It lets an LLM agent (Claude, or any MCP client) train, deploy, optimise, and explain transparent machine-learning models through a small set of goal-oriented
No automated test available for this server. Check the GitHub README for setup instructions.
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
No package registry to scan.
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