Quickstart¶
Get jquants-mcp answering Japanese stock questions in your MCP client in about 5 minutes.
Prerequisites¶
- Python 3.10 or newer (
python3 --version) - A J-Quants account with at least the Free plan (Light or above unlocks daily bars beyond the 12-week delay)
- One of: Claude Code (CLI), Claude Desktop, Codex, or any MCP-aware client
1. Install jquants-mcp¶
2. Get your J-Quants API key¶
The easiest way is the built-in browser login (PKCE flow):
This opens the J-Quants OAuth page; after approving, the API key is saved
to ~/.config/jquants-mcp/config.ini (mode 0600). Run jquants-mcp logout
to clear it.
If you prefer to manage the key yourself, copy it from the J-Quants dashboard and put it in the same file:
JQUANTS_API_KEY env var also works if you would rather not write a config file.
3. Connect your client¶
- Open claude.ai and create a Project (left sidebar → Projects → New project).
- Open the project → gear icon → Integrations → Add integration → Custom → enter the URL of the gateway fronting your jquants-mcp server (e.g. a Cloud Run deployment). jquants-mcp itself speaks only stdio, so remote clients always connect through a gateway — the reference Cloud Run setup signs you in with your Google account.
- (Optional but recommended) Click Add instructions and paste
the contents of
docs/claude-project-instructions.md. This teaches Claude how to render React artifact charts from the tool output without extra prompting. - The project settings (including the MCP connection) sync automatically to the Claude mobile app within a few minutes.
This repository doubles as a single-plugin marketplace, so Claude Code can install the server for you:
The plugin launches uvx, so it must be on the PATH of the process
that runs Claude Code — a login shell usually has it, but a
GUI-launched app may not; install uv
system-wide if the plugin fails to start.
Reads the same environment variables as
step 2 above. The plugin's own
.mcp.json intentionally leaves out JQUANTS_API_KEY so the key you
just set up — ~/.config/jquants-mcp/config.ini from jquants-mcp
login, or a pre-existing ~/.jquants-api/jquants-api.toml — is still
found; export JQUANTS_API_KEY yourself before starting Claude Code
only if you'd rather override both of those.
Verify with claude mcp list. The next time you launch claude, the
server is available.
Edit ~/Library/Application Support/Claude/claude_desktop_config.json
(macOS) or the equivalent on Windows / Linux:
Restart Claude Desktop to pick up the change.
Verify with codex mcp list. The next Codex session has the tools.
Any MCP client that launches local stdio servers works the same way:
use jquants-mcp as the command. Web-based clients such as Meta Muse
instead connect to a remote deployment over OAuth — see the
deployment guide; the gateway must allow that client's
OAuth callback (--allow-redirect-uri).
4. Try it out¶
Open your client and ask:
今日の業種別騰落率を教えて
The agent calls get_sector_performance and returns a ranked sector table. The
first call seeds the local cache; subsequent queries are instant.
Try a chart:
キオクシア(285A)のチャートを 3 か月分
The agent calls get_candlestick_data and returns the candles; on claude.ai it renders them as a candlestick React artifact inline.
Next steps¶
- Tools → — what else you can ask for.
- FAQ → — common errors, plan recommendations, multi-user mode.
- Full reference: GitHub README covers config schema, deployment shapes (Docker / Cloud Run / gateway-fronted self-hosting), per-tool parameter tables, and the gateway-side authentication setup.