No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by pyroprompts · MCP Server · ★ 155
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is any-chat-completions-mcp safe to install? View the security audit →
any-chat-completions-mcp MCP Server Integrate Claude with Any OpenAI SDK Compatible Chat Completion API - OpenAI, Perplexity, Groq, xAI, PyroPrompts and more. This implements the Model Context Protocol Server. Learn more: https://modelcontextprotocol.io This is a TypeScript-based MCP server that implements an implementation into any OpenAI SDK Compatible Chat Completions API. It has one tool, which relays a question to a configured AI Chat Provider. Development Install dependencies: Build the server: For development with auto-rebuild: Installation To add OpenAI to Claude Desktop, add the server config: On MacOS: On Windows: You can use it via in your Claude Desktop configuration like this: json { "mcpServers": { "chat-openai": { "command": "npx", "args": [ "@pyroprompts/any-chat-completions-mcp" ], "env": { "AICHATKEY": "OPENAIKEY", "AICHATNAME": "OpenAI", "AICHATMODEL": "gp
| Stars | 155 |
| Forks | 27 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.146346436303/100 |
| Open Issues | 8 |
| Last Updated | 2025-05-01 |
| Created | 2024-12-02 |
| Platforms | mcp, node |
| Est. Tokens | ~1518k |
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any-chat-completions-mcp is MCP Server for using any LLM as a Tool. It is categorized as a MCP Server with 155 GitHub stars.
any-chat-completions-mcp is primarily written in JavaScript. It covers topics such as mcp, mcp-server.
You can find installation instructions and usage details in the any-chat-completions-mcp GitHub repository at github.com/pyroprompts/any-chat-completions-mcp. The project has 155 stars and 27 forks, indicating an active community.
any-chat-completions-mcp is released under the MIT license, making it free to use and modify according to the license terms.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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