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From wet-mcp
Connects to multiple AI model providers (OpenAI, Gemini, Cohere, Jina AI) for LLM queries, embeddings, and reranking. Integrates with GitHub. Requires API keys for each provider.
Copy this JSON into your .mcp.json to enable this server
Add to your .mcp.json:
{
"mcpServers": {
"wet": {
"command": "uvx",
"args": [
"--python",
"3.13",
"wet-mcp"
],
"env": {
"LLM_MODELS": "${user_config.LLM_MODELS}",
"GITHUB_TOKEN": "${user_config.GITHUB_TOKEN}",
"MCP_TRANSPORT": "stdio",
"RERANK_MODELS": "${user_config.RERANK_MODELS}",
"COHERE_API_KEY": "${user_config.COHERE_API_KEY}",
"GEMINI_API_KEY": "${user_config.GEMINI_API_KEY}",
"OPENAI_API_KEY": "${user_config.OPENAI_API_KEY}",
"JINA_AI_API_KEY": "${user_config.JINA_AI_API_KEY}",
"EMBEDDING_MODELS": "${user_config.EMBEDDING_MODELS}"
}
}
}
}Replace placeholder values for: GITHUB_TOKEN, COHERE_API_KEY, GEMINI_API_KEY
Review these signals before enabling this server
This MCP server needs API keys or credentials. Configure them in your environment before use.
Server configuration and connection parameters
uvxCommand-line arguments passed to the server process
Environment variables set when the server starts
LLM_MODELS=${user_config.LLM_MODELS}GITHUB_TOKEN=${user_config.GITHUB_TOKEN}MCP_TRANSPORT=stdioRERANK_MODELS=${user_config.RERANK_MODELS}COHERE_API_KEY=${user_config.COHERE_API_KEY}GEMINI_API_KEY=${user_config.GEMINI_API_KEY}OPENAI_API_KEY=${user_config.OPENAI_API_KEY}JINA_AI_API_KEY=${user_config.JINA_AI_API_KEY}EMBEDDING_MODELS=${user_config.EMBEDDING_MODELS}Sensitive values you must provide — never committed to source control
npx claudepluginhub n24q02m/wet-mcp