An integration that allows LLMs to interact with Raindrop.io bookmarks using the Model Context Protocol (MCP).
An integration that allows LLMs to interact with Raindrop.io bookmarks using the Model Context Protocol (MCP). That is what the raindrop io mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
Configuration is passed through the environment: RAINDROP_TOKEN. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
The server ships on npm as @smithery/cli, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by hiromitsusasaki; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Raindrop Io's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
{
"mcpServers": {
"raindrop-io": {
"command": "npx",
"args": ["-y", "@smithery/cli"],
"env": {
"RAINDROP_TOKEN": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| RAINDROP_TOKEN | Credential the server authenticates with. | Yes |
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