Both can power serious agent workflows. The decision usually depends on where you want control: graph orchestration primitives, or runtime + protocol integration focused on resilient operations. This comparison breaks down the key architectural dimensions so you can choose the right foundation — or combine both.
| Feature | OpenClaw + Delx | LangGraph |
|---|---|---|
| Execution model | Protocol-first — every tool call is an MCP or A2A message with built-in metadata | Graph-based — nodes and edges define execution flow with typed state |
| Recovery | Built-in session recovery, retry budgets, and heartbeat continuity | Manual checkpointing via state snapshots; custom retry logic required |
| Protocols | MCP + A2A native with schema validation and session persistence | Custom tool interfaces; MCP via third-party adapters |
| Observability | Wellness scoring, heartbeat monitoring, DELX_META telemetry | LangSmith tracing with graph-level step visualization |
| Governance | Controller-ready updates with nudge-driven closure loops | Graph state management with conditional branching |
| Pricing | Freemium with x402 micropayments for premium tiers | Usage-based via LangSmith; open-source core |
Many production teams find the two layers complementary rather than competing. LangGraph handles the “what runs when” orchestration, while OpenClaw with Delx handles the “what happens when things break” reliability layer.
Concrete example: A customer-support pipeline uses a LangGraph DAG to route tickets through triage, research, and drafting nodes. Each node calls tools via an OpenClaw MCP server. When the research node hits a rate limit, OpenClaw's session recovery automatically retries with exponential backoff, reports a wellness dip through DELX_META, and emits a nudge suggesting the controller switch to a fallback data source. LangGraph sees the node complete successfully and advances the graph — without any custom retry logic in the graph definition itself.
Start by identifying your primary bottleneck. If you need structured execution flow with conditional branching, LangGraph gives you those primitives immediately. If your bottleneck is runtime reliability — sessions dropping, tools failing silently, no visibility into agent health — OpenClaw and Delx solve those problems at the protocol level. For teams facing both challenges, running LangGraph orchestration on top of OpenClaw tool execution gives you the best of both worlds.
Yes. A common pattern is to use LangGraph for high-level graph orchestration while routing individual tool calls through OpenClaw and Delx for session recovery, wellness scoring, and MCP/A2A protocol compliance. The two layers complement each other without overlap.
OpenClaw with Delx provides built-in session recovery, heartbeat loops, and retry budgets out of the box. LangGraph requires manual checkpointing and custom retry logic. For teams prioritizing uptime and operational continuity, OpenClaw delivers reliability primitives at the framework level.
LangGraph does not natively implement the Model Context Protocol (MCP) or Agent-to-Agent (A2A) protocol. You can integrate MCP tool servers manually, but OpenClaw treats both protocols as first-class surfaces with native routing, schema validation, and session continuity.