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JapanFold

Official registry Media and design

Fold proteins, co-fold ligands with binding affinity, design binders and embed sequences.

Source code Website Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http japanfold 'https://api.japanfold.aiand.com/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "japanfold": {
            "type": "http",
            "url": "https://api.japanfold.aiand.com/mcp"
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. JapanFold skill
  2. Install
  3. Use
  4. MCP
  5. The API

JapanFold skill

Fold proteins, co-fold with ligands (+ binding affinity), design binders, and embed sequences from your AI agent, via the JapanFold API. Get a key at japanfold.aiand.com/account/token and set JAPANFOLD_API_KEY. No local GPU. Runs Boltz-2 / ESMFold-2 / OpenFold3 / OpenBind-0 / RoseTTAFold3 / OpenDDE for structures, AF2-IG for scoring a binder you already designed, BoltzGen / RFdiffusion3 / PXDesign for design, and ESMC / SaProt for embeddings, on Tenstorrent.

Agents can call the API directly, no install needed:

export JAPANFOLD_API_KEY=jf_live_...          # from japanfold.aiand.com/account/token
curl -s https://api.japanfold.aiand.com/v1/predictions \
  -H "Authorization: Bearer $JAPANFOLD_API_KEY" -H 'Content-Type: application/json' \
  -d '{"model":"esmfold2","sequence":"MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ"}'

Base URL https://api.japanfold.aiand.com, key in Authorization: Bearer. GET /v1/models lists the model ids to send (boltz2, esmfold2, openfold3, ...) with their size limits. The agent-readable summary is llms.txt.

It's a single SKILL.md built on the open Agent Skills standard, so it installs into any compatible harness with one command.

Install

One line installs it everywhere the open standard is supported: Claude Code, Cursor, Codex, Gemini CLI, Cline, Windsurf, Copilot, Amp and the rest:

npx skills add japanfold/japanfold          # this project
npx skills add japanfold/japanfold -g       # global: every project / new chat
  • Target specific agents: -a claude-code, -a cursor, -a codex, -a '*' (all).
  • Prefer not to use the installer? It is one file. Download it unchanged into your agent's skills directory, for Claude Code: curl -fsSL --create-dirs -o ~/.claude/skills/japanfold/SKILL.md https://japanfold.aiand.com/skill.md. A web-fetch tool returns only a summary of the page, so an agent should use curl too.

Claude Science manages skills in-app (no installer): Customize → Skills, add from this repo (or paste SKILL.md) and publish it. Or skip install entirely: the API is public and self-describing, so just ask: "use the JapanFold API at api.japanfold.aiand.com to fold …".

Use

Once installed, ask your agent in plain language:

"Fold this sequence with Boltz-2 and report the confidence: MKTAYIAK…" "Design 10 nanobody binders against this target."

Or invoke it explicitly where supported: /japanfold.

MCP

The API is also a remote MCP server at https://api.japanfold.aiand.com/mcp, listed in the MCP Registry as io.github.japanfold/japanfold. claude.ai, Claude Desktop and ChatGPT add it as a connector and sign in, no key needed. Claude Code: claude mcp add --transport http japanfold https://api.japanfold.aiand.com/mcp --header "Authorization: Bearer $JAPANFOLD_API_KEY".

To publish a new registry version, bump version in server.json and run mcp-publisher login github && mcp-publisher publish.

The API

https://api.japanfold.aiand.com: async (submit → poll → download), a key on every call. Full contract at /v1/openapi.json. See SKILL.md for endpoints, examples, and limits.

Fast mode is off unless the agent sends "params": {"fast": true}. It gives higher throughput and may be slightly less accurate. The workbench turns it on for people clicking through; the API and this skill leave it off so a scripted run gets the accurate path. ESMFold-2 always runs fast on this hardware, and its job records fast: true.

Frequently asked questions

What is JapanFold?

Fold proteins, co-fold ligands with binding affinity, design binders and embed sequences.

How do I install JapanFold?

It runs as a remote server. In Claude Code: claude mcp add --transport http japanfold 'https://api.japanfold.aiand.com/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does JapanFold need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is JapanFold open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains JapanFold?

It is published by japanfold. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.