A LangGraph agent that subscribes to EEP entity streams, handles gates (auth/payment/agreement), and processes events using Claude.

1. Discovery: Agent resolves an entity via Layer 1 REST, reads Link headers and /.well-known/eep.json.
2. Subscription: Agent subscribes to entity events via POST /eep/subscribe (Layer 2 webhook delivery).
3. Gate handling: When the agent hits a 402 access_restricted or 403 access_forbidden response, it parses the canonical unmet_requirements[] (each carries a machine-readable resolution_hint) and constructs a matching gate proof per requirement — no LLM needed to decide what to do.
4. Event processing: Incoming webhook events are validated against the CloudEvents envelope and signature-checked with a Standard Webhooks HMAC verifier (the algorithm in eep-signer), then routed to a LangGraph processing graph.

This example implements the EEP wire contracts (canonical gate response, Standard Webhooks HMAC) inline so it reads as a single self-contained file. In production, import eep-gates, eep-signer, and eep-validator instead of re-implementing them.

5. Claude reasoning: Each event is summarized and acted on by Claude (via langchain-anthropic).

EEP Publisher
    │
    ├─ Layer 1 (GET /u/acme-corp) → discovery + gate requirements
    ├─ Layer 2 (POST /eep/subscribe) → webhook subscription
    │
    └─ Webhook delivery ──────┐
                              ▼
                    ┌─────────────────┐
                    │  LangGraph Agent │
                    │  ┌─────────────┐ │
                    │  │ validate    │ │  ← eep-validator-python
                    │  │ verify sig  │ │  ← eep-signer-python
                    │  │ gate check  │ │  ← eep-gates-python
                    │  │ Claude LLM  │ │  ← langchain-anthropic
                    │  │ act/respond │ │
                    │  └─────────────┘ │
                    └─────────────────┘

• Python 3.11+
• An ANTHROPIC_API_KEY environment variable
• A running EEP publisher (use the reference implementation or the realworld simulation)

cd EEP/examples/langgraph-eep-agent
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

# Point at a running EEP publisher
export EEP_TARGET=http://localhost:3100
export ANTHROPIC_API_KEY=sk-ant-...

python agent.py

Both 402 access_restricted and 403 access_forbidden use the same canonical body (gate.402-response.json / gate.403-response.json):

{
  "error": "access_restricted",
  "resource": "content.papers.full_text",
  "current_tier": "free",
  "required_tier": "paid",
  "unmet_requirements": [
    { "type": "payment", "amount": 0.1, "currency": "USD", "per": "request",
      "resolution_hint": "Pay $0.10 via the payment_methods URL" }
  ]
}

handle_gate_challenge() iterates unmet_requirements and builds one proof per entry, routed on each requirement's type (payment → token, credential → a VC in the accepted format, agreement → a signature over document_hash, identity/trust/connection, …). Every requirement carries a resolution_hint, so the agent decides what to satisfy without an LLM call. Requirement types the demo cannot auto-satisfy (e.g. custom x-*) are skipped.

test_agent.py asserts this parsing against the canonical shapes (run python -m pytest test_agent.py).

• EEP Specification
• MCP-EEP Bridge Guide
• Agent Onboarding Guide
• Realworld Simulation