Epicure Server

Epicure is a public, anonymous, read-only Model Context Protocol server for computational flavour exploration. It exposes deterministic tools over 1,790 ingredient embeddings learned from a 4.14 million-recipe, multilingual corpus.

• MCP endpoint: https://epicure-mcp.kaikaku.ai/mcp
• Health check: https://epicure-mcp.kaikaku.ai/healthz
• Interactive guide: epicure.kaikaku.ai/agents
• Authentication: none
• Transport: Streamable HTTP

The production origin runs on KAIKAKU's local compute cluster and is published through a Cloudflare Tunnel. It is not hosted on Google Cloud or Azure. Every tool reads the bundled model artefacts; the MCP server makes no external AI or data-provider calls.

Connect from Claude

In Claude, open Settings → Connectors → Add custom connector and enter:

Name: Epicure
URL:  https://epicure-mcp.kaikaku.ai/mcp
Auth: None

Try one of these prompts after enabling the connector:

• “Use Epicure to build a vegan pairing graph around tomato and basil.”
• “Compare miso and soy sauce on the savoury axis.”
• “What ingredients are nearest to saffron in Epicure’s flavour space?”
• “Move rice 30 degrees toward the South Asian cuisine direction.”
• “Show where yuzu sits on Epicure’s ingredient atlas.”
• “Find a flavour trade-off from miso along a coherent factor.”

Tool outputs describe learned statistical relationships. They are not food safety, allergy, medical, or nutritional advice.

Tools

All tools advertise read-only, non-destructive, idempotent, closed-world MCP annotations and validated JSON schemas.

Tool title	MCP name	Purpose
Compare ingredients on an axis	compare_on_axis	Compare two ingredients along a named flavour, cuisine, nutrient, diet, or processing axis.
Score an ingredient pairing	pairing_score	Measure cosine affinity for one exact ingredient pair.
Explore ingredient pairings	find_pairings	Build a diversified cluster-and-bridge pairing graph for one or more seeds.
Inspect flavour correlations	flavour_correlations	Return the strongest relationships between named flavour-space axes.
Profile an ingredient by cuisine	cultural_profile	Measure an ingredient against the bundled cuisine directions.
Find similar ingredients	neighbors	Return nearest ingredients in the 300-dimensional embedding.
Transform an ingredient in flavour space	morph	Rotate a seed toward a direction, mode, or ingredient using spherical interpolation.
List transformation targets	list_targets	Page through valid directions and emergent modes for morph.
List flavour factors	list_factors	Inspect the 20 named ICA factor summaries, with examples available on request.
Project an ingredient onto a factor	ingredient_on_factor	Measure signed position on an ICA factor.
Navigate a flavour trade-off	pareto_navigate	Find ingredients on a proximity-versus-factor Pareto frontier.
Find an ingredient’s flavour region	closest_mode	Find the closest named GMM modes.
Locate an ingredient on the atlas	where_on_atlas	Return the precomputed atlas coordinate and nearby 2-D peers.

Large catalogues are filtered and paginated. Default responses are deliberately compact; callers can request more detail through each tool's documented inputs.

Data and privacy

Epicure has no accounts, cookies, user profiles, or advertising. Tool arguments and result content are processed in memory and are never written to application logs. Minimal operational telemetry contains a rotating pseudonymous client hash, tool name, response size, latency, success state, and exception class.

Read the complete Privacy Policy, Security Policy, Support Policy, and Terms.

Architecture

MCP client
    │  HTTPS / Streamable HTTP
    ▼
Cloudflare edge (TLS, DDoS controls, WAF/rate limits)
    │  outbound-only Cloudflare Tunnel
    ▼
reef-cluster on local KAIKAKU compute
    └── epicure-mcp container
          └── bundled read-only model artefacts

The origin binds to loopback on the cluster host. No inbound router port is opened; cloudflared initiates the tunnel from the private Docker network. See docs/DEPLOYMENT.md for operations and docs/CLAUDE_SUBMISSION.md for the directory listing.

Local development

Python 3.11 or newer is supported (production uses Python 3.12).

python3.12 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
python scripts/verify_data.py --data-dir data
ruff check src tests scripts
pytest -q
python -m epicure_mcp.server

The local endpoints are:

Path	Method	Purpose
/healthz	GET	Lightweight liveness probe.
/mcp	POST/GET/DELETE	Streamable HTTP MCP transport.
/atlas	GET	Read-only 3-D UMAP projection used by the Epicure site.
/favicon.ico, /favicon.png	GET	Connector icon.

Inspect the local server with the official MCP Inspector:

npx -y @modelcontextprotocol/inspector \
  --cli http://127.0.0.1:8080/mcp --transport http --method tools/list

Run the complete remote smoke suite against production:

python scripts/smoke_test_remote.py https://epicure-mcp.kaikaku.ai/mcp

Configuration

Variable	Default	Purpose
EPICURE_DATA_DIR	<repo>/data	Bundled artefact directory.
EPICURE_ASSETS_DIR	bundled assets	Optional favicon directory.
HOST	0.0.0.0	Bind address.
PORT	8080	Bind port.
RATE_LIMIT_PER_MINUTE	60	Per-client token refill rate.
RATE_LIMIT_BURST	10	Per-client burst capacity.
MCP_SERVER_NAME	Epicure	Name in the MCP initialize response.
MCP_API_TOKEN	unset	Optional bearer token for private deployments. Production leaves this unset.
MCP_ALLOWED_HOSTS	production + local hosts	Comma-separated DNS-rebinding allowlist.
MCP_ALLOWED_ORIGINS	Claude, Epicure + local origins	Comma-separated browser-origin allowlist.

Bundled artefacts

The repository includes the model bundle, so production does not depend on an upstream service at runtime. It contains embeddings and ingredient metadata, supervised directions, ICA factors, GMM modes, and 2-D/3-D UMAP projections. Validate shape and presence with scripts/verify_data.py after any refresh.

License

MIT © KAIKAKU.AI Limited.