moatdrop-mcp 0.3.0

MCP server for Moatdrop — manage secure links from AI assistants

Moatdrop MCP Server

An MCP (Model Context Protocol) server for Moatdrop — manage secure, trackable links from AI assistants like Claude Desktop, Cursor, and Claude Code.

Installation

pip install moatdrop-mcp

Or run directly with uvx:

uvx moatdrop-mcp

Setup

1. Get an API Key

1. Log in to Moatdrop
2. Go to Account > API Keys
3. Create a new key and copy it

2. Configure Your AI Assistant

Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "moatdrop": {
      "command": "uvx",
      "args": ["moatdrop-mcp"],
      "env": {
        "MOATDROP_API_KEY": "mdp_your_key_here"
      }
    }
  }
}

Cursor

Add to your Cursor MCP config (.cursor/mcp.json):

{
  "mcpServers": {
    "moatdrop": {
      "command": "uvx",
      "args": ["moatdrop-mcp"],
      "env": {
        "MOATDROP_API_KEY": "mdp_your_key_here"
      }
    }
  }
}

Claude Code

claude mcp add moatdrop -- uvx moatdrop-mcp

Then set the environment variable:

export MOATDROP_API_KEY="mdp_your_key_here"

Environment Variables

Variable	Required	Default	Description
MOATDROP_API_KEY	Yes	—	Your Moatdrop API key (mdp_...)
MOATDROP_API_URL	No	https://api.moatdrop.com	API base URL (for self-hosted or dev)

Available Tools

Link Management

Tool	Description
create_link	Create a secure link with URL, expiration, IP rules, click limits
list_links	List all your secure links
get_link	Get full details of a specific link
update_link	Update link name, expiration, click limits
delete_link	Permanently delete a link (requires confirm=true)
enable_link	Re-enable a revoked link
disable_link	Revoke/disable a link

Document Queries

Tool	Description
deep_extraction	Ask a question and get an AI-synthesized answer from a shared file

Analytics & Account

Tool	Description
get_link_analytics	Get raw access logs for a link
get_analytics_summary	Aggregated analytics: clicks, unique IPs, top countries, referrers
get_account_info	Your account details and plan tier

Available Resources

URI	Description
moatdrop://links	Summary list of all your links
moatdrop://links/{id}	Full details for a specific link
moatdrop://links/{id}/analytics	Access logs for a specific link
moatdrop://account	Your account info

Querying Files with AI Agents

MoatDrop lets you upload files, create secure links, and then query those files through AI agents using the MCP server. Here's how to set it up end to end.

Step 1: Upload a file and create a secure link

Log in to MoatDrop, click + Create Moat Link, and upload your file (PDF, DOCX, XLSX, etc.). Once created, note the moat link — this is the short code in the secure URL (e.g., if the URL is https://moatdrop.com/l/abc123, the moat link is abc123).

You can find the moat link on the link detail page under Moat Link.

Step 2: Create a share token

Share tokens let you grant someone query-only access to a specific file without sharing your full API key.

1. Go to the link detail page for your file
2. Expand AI Agent Access > Show Setup
3. Under Create Share Token, enter a name (e.g., "For Acme Corp")
4. Optionally set an expiration (hours) and max uses
5. Click Create Token
6. Copy the token (starts with mds_) — it's shown only once

Step 3: Configure the MCP server

Give the share token to whoever needs to query the file. They add this to their AI assistant config:

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "moatdrop": {
      "command": "uvx",
      "args": ["moatdrop-mcp"],
      "env": {
        "MOATDROP_API_KEY": "mds_your_share_token_here"
      }
    }
  }
}

Cursor / VS Code

Add to .cursor/mcp.json or VS Code MCP settings:

{
  "mcpServers": {
    "moatdrop": {
      "command": "uvx",
      "args": ["moatdrop-mcp"],
      "env": {
        "MOATDROP_API_KEY": "mds_your_share_token_here"
      }
    }
  }
}

Claude Code

claude mcp add moatdrop -- uvx moatdrop-mcp

Then set the environment variable:

export MOATDROP_API_KEY="mds_your_share_token_here"

Step 4: Query the file

Once connected, ask your AI assistant to query the file using the moat link:

Deep extraction (AI-synthesized answers):

"Use the deep_extraction tool with moat_link abc123 and ask: What are the key findings in this report?"

The tool sends the full document to Gemini in a single call and returns a synthesized answer with PII scrubbed.

Share token vs API key

	Share Token (mds_)	API Key (mdp_)
Scope	Query access to one specific file	Full account access
Safe to share	Yes	No
Can manage links	No	Yes
Can view analytics	No	Yes
Expiration	Optional (configurable)	Optional
Usage limits	Optional (configurable)	None

Examples

Once configured, you can ask your AI assistant:

• "Use deep_extraction with hash abc123: What is the executive summary?"
• "Use deep_extraction with hash abc123: What date was the contract signed?"
• "Use deep_extraction with hash abc123: Pull the termination clauses from this contract"

Development

# Clone and install in dev mode
cd mcp-server
pip install -e .

# Run with a local backend
MOATDROP_API_KEY=mdp_test MOATDROP_API_URL=http://localhost:8000 moatdrop-mcp

# Run tests
pip install pytest
pytest tests/

License

MIT