wet

{
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "name": "io.github.n24q02m/wet",
  "description": "Open-source MCP server for AI agents: web search, content extraction, and library docs.",
  "repository": {
    "url": "https://github.com/n24q02m/wet.git",
    "source": "github"
  },
  "version": "3.19.2",
  "packages": [
    {
      "registryType": "pypi",
      "identifier": "wet-mcp",
      "version": "3.19.2",
      "runtimeHint": "uvx",
      "transport": {
        "type": "stdio"
      },
      "environmentVariables": [
        {
          "description": "Provider API keys (format: PROVIDER_API_KEY:key,...). Select models per task with EMBEDDING_MODELS / RERANK_MODELS / LLM_MODELS (CSV provider/model, order = litellm fallback); provider is inferred from the model prefix. Empty embedding/rerank chain falls back to fastretrieval's built-in local reference model.",
          "isSecret": true,
          "name": "API_KEYS"
        },
        {
          "description": "GitHub personal access token for higher rate limits on library discovery",
          "isSecret": true,
          "name": "GITHUB_TOKEN"
        }
      ]
    }
  ]
}