About papertax
Hyperliquid tax reports and Koinly/CTC exports for agents
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
Endpoint
https://papertax.xyz/mcpCopy install command
Claude CodeTerminal
claude mcp add --transport http awakeweb3-papertax https://papertax.xyz/mcpCursor.cursor/mcp.json
{"mcpServers":{"awakeweb3-papertax":{"type":"http","url":"https://papertax.xyz/mcp"}}}Open in CursorVS Code.vscode/mcp.json
{"servers":{"awakeweb3-papertax":{"type":"http","url":"https://papertax.xyz/mcp"}}}Open in VS CodeClaude Desktopclaude_desktop_config.json
{"mcpServers":{"awakeweb3-papertax":{"type":"http","url":"https://papertax.xyz/mcp"}}}Windsurf~/.codeium/windsurf/mcp_config.json
{"mcpServers":{"awakeweb3-papertax":{"serverUrl":"https://papertax.xyz/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
All endpoints
Streamable HTTP
https://papertax.xyz/mcpAuth requiredTools
6| Parameter | Type | Required | Description |
|---|---|---|---|
| sample | boolean | No | Return deterministic sample data instead of reading Hyperliquid |
| address | string | Yes | Public Hyperliquid wallet address |
| tax_year | enum | No | Tax year. AU-2027 = Australia · FY 2026–27; AU-2026 = Australia · FY 2025–26; US-2026 = United States · 2026; US-2025 = United States · 2025; UK-2027 = United Kingdom · 2026–27; UK-2026 = United Kingdom · 2025–26; CA-2026 = Canada · 2026; CA-2025 = Canada · 2025; NZ-2027 = New Zealand · 2026–27; NZ-2026 = New Zealand · 2025–26. Defaults to the year being filed now.AU-2027 | AU-2026 | US-2026 | US-2025 | UK-2027 | UK-2026 | CA-2026 | CA-2025 | NZ-2027 | NZ-2026 |
| jurisdiction | enum | No | Used when tax_year is not given. AU = 1 Jul–30 Jun; US and CA = calendar year; UK = 6 Apr–5 Apr; NZ = 1 Apr–31 MarAU | US | UK | CA | NZ |
Details
The maintainer has not added details yet. Check the README in the repository.
Comments
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.