OpenClaw 2026.3.1: WebSocket Streaming, Agent Routing, and K8s Support

OpenClaw just dropped version 2026.3.1 — and this one matters. WebSocket-first streaming for OpenAI models, native Kubernetes health checks, a proper agent routing CLI, and Claude 4.6 adaptive thinking enabled by default.

If you’re running OpenClaw in production or considering it for your AI agent workflow, this guide covers every meaningful change in the release, what it means for your setup, and how to configure the new features.

What Changed: The Big Picture

OpenClaw 2026.3.1 is a production-readiness release. While previous versions focused on expanding platform integrations and agent capabilities, this release is about making OpenClaw faster, more manageable, and easier to deploy at scale.

Here’s the TL;DR:

Let’s break each one down.

WebSocket-First Transport for OpenAI

This is arguably the biggest performance change in 2026.3.1. OpenClaw now uses WebSocket as the default transport for OpenAI Responses API, with SSE (Server-Sent Events) as a fallback.

Why This Matters

The old SSE transport opens a new HTTP connection for every response stream. WebSocket maintains a persistent connection, which means:

• Lower latency: No connection setup overhead per request
• Faster token delivery: Tokens arrive in real-time over the persistent connection
• Better agent handoffs: Multi-step reasoning chains execute faster
• Reduced server load: Fewer connections to manage

Think of it like the difference between sending individual letters (SSE) versus having an open phone line (WebSocket). The phone line is always ready — no dialing, no waiting.

Configuration

WebSocket is enabled by default with transport: "auto". To explicitly control it:

# In your openclaw config
[response]
# "auto" = WebSocket with SSE fallback (default)
# "websocket" = WebSocket only
# "sse" = SSE only (legacy behavior)
transport = "auto"

# Optional: Enable warm-up for specific models
[response.openaiWsWarmup]
"gpt-5" = true
"gpt-4.1" = false

The warm-up feature (response.create with generate:false) pre-establishes the WebSocket connection before you need it, eliminating even the initial connection delay.

When to Use SSE Fallback

Stick with SSE if:

• Your network/firewall blocks WebSocket connections
• You’re behind a proxy that doesn’t support WebSocket upgrades
• You need maximum compatibility with older infrastructure

Claude 4.6 Adaptive Thinking

OpenClaw 2026.3.1 enables adaptive thinking by default for all Anthropic Claude 4.6 models. Other reasoning-capable models keep the "low" setting unless you configure otherwise.

What Is Adaptive Thinking?

Instead of applying the same reasoning depth to every request, adaptive thinking lets Claude dynamically adjust how much it “thinks” based on task complexity:

• Simple question → Quick, direct answer (fewer tokens)
• Complex multi-step reasoning → Deep analysis with extended thinking (more tokens, better quality)
• Tool-use chains → Balanced approach optimized for sequential tool calls

This is like having a developer who knows when to quickly fix a typo versus when to carefully architect a system redesign.

Configuration

[agents.default.model]
provider = "anthropic"
name = "claude-4.6-sonnet"

[agents.default.model.thinking]
# "adaptive" = model decides depth (default for Claude 4.6)
# "low" = minimal reasoning (faster, cheaper)
# "high" = maximum reasoning (slower, more expensive)
mode = "adaptive"

For agents that handle routine tasks (notifications, simple lookups), you might want to force "low" to save tokens:

[agents.notification-bot.model.thinking]
mode = "low"

For complex agents handling multi-step workflows, "adaptive" (the default) usually makes the right call automatically.

Kubernetes Health Endpoints

If you’ve tried deploying OpenClaw on Kubernetes before, you know the pain. No native health checks meant you were writing custom probe scripts or relying on TCP checks. Not anymore.

New Endpoints

OpenClaw 2026.3.1 adds four HTTP health endpoints:

Kubernetes Deployment Example

Here’s a production-ready deployment manifest:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: openclaw-gateway
spec:
  replicas: 2
  selector:
    matchLabels:
      app: openclaw
  template:
    metadata:
      labels:
        app: openclaw
    spec:
      containers:
      - name: openclaw
        image: openclaw/openclaw:2026.3.1
        ports:
        - containerPort: 18789
        env:
        - name: OPENCLAW_HOME
          value: "/data/openclaw"
        livenessProbe:
          httpGet:
            path: /healthz
            port: 18789
          initialDelaySeconds: 15
          periodSeconds: 20
          failureThreshold: 3
        readinessProbe:
          httpGet:
            path: /readyz
            port: 18789
          initialDelaySeconds: 5
          periodSeconds: 10
        resources:
          requests:
            memory: "512Mi"
            cpu: "250m"
          limits:
            memory: "2Gi"
            cpu: "1000m"
        volumeMounts:
        - name: openclaw-data
          mountPath: /data/openclaw
      volumes:
      - name: openclaw-data
        persistentVolumeClaim:
          claimName: openclaw-pvc

Docker Compose Health Check

For Docker Compose deployments:

services:
  openclaw:
    image: openclaw/openclaw:2026.3.1
    ports:
      - "18789:18789"
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:18789/healthz"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 15s
    volumes:
      - openclaw-data:/data/openclaw

Agent Routing CLI

Managing which agent handles which messaging account used to require manual config file editing. The new agent routing CLI makes this a first-class operation.

New Commands

# List all agent-to-account bindings
openclaw agents bindings

# Bind an agent to a specific account
openclaw agents bind --agent research-bot --account whatsapp-main

# Unbind an agent from an account
openclaw agents unbind --agent research-bot --account whatsapp-main

# Add a new channel with optional account binding prompt
openclaw channels add --type telegram --bind-agent my-agent

How Routing Works

Agent routing lets you run multiple specialized agents on the same OpenClaw instance, each handling different messaging accounts or channels:

┌─────────────────────────────────────────┐
│              OpenClaw Gateway            │
│                                         │
│  ┌─────────┐  ┌──────────┐  ┌────────┐ │
│  │Research  │  │Assistant │  │DevOps  │ │
│  │Agent     │  │Agent     │  │Agent   │ │
│  └────┬─────┘  └────┬─────┘  └───┬────┘ │
│       │             │            │      │
│  ┌────▼─────┐  ┌────▼─────┐ ┌───▼────┐ │
│  │WhatsApp  │  │Telegram  │ │Discord │ │
│  │Personal  │  │Team Chat │ │DevOps  │ │
│  └──────────┘  └──────────┘ └────────┘ │
└─────────────────────────────────────────┘

Each agent can have its own model, system prompt, tools, and security profile. Routing ensures messages go to the right agent automatically.

Practical Example

Say you want a research agent on WhatsApp and a DevOps agent on Discord:

# Create agents with different configs
openclaw agents bind --agent research-bot --account whatsapp-personal
openclaw agents bind --agent devops-bot --account discord-engineering

# Verify bindings
openclaw agents bindings
# Output:
# research-bot  → whatsapp-personal (active)
# devops-bot    → discord-engineering (active)

For more on multi-agent patterns, see our OpenClaw Multi-Agent Guide.

External Secrets Management

OpenClaw 2026.3.1 introduces a complete secrets management workflow — critical for production deployments where you can’t just put API keys in plaintext config files.

The openclaw secrets CLI

# Audit current secrets configuration
openclaw secrets audit

# Configure a new secrets provider
openclaw secrets configure --provider vault --endpoint https://vault.example.com

# Apply secrets from the provider
openclaw secrets apply --target agents/research-bot/auth-profiles.json

# Reload secrets without restarting the gateway
openclaw secrets reload

Supported Providers

The external secrets system integrates with:

• AWS Secrets Manager — for AWS-native deployments
• HashiCorp Vault — for multi-cloud or on-prem
• File-backed secrets (~/.openclaw/secrets.json) — for simple setups
• Environment variables — for container deployments

Why This Matters

Before this release, managing credentials across multiple agents, models, and channels was a mess. API keys for OpenAI, Anthropic, messaging platforms — all scattered across config files with different formats.

External secrets management gives you:

• Centralized rotation: Change a key once, all agents pick it up
• Least-privilege access: Each agent only sees the credentials it needs
• Audit trails: Track which agent accessed which secret and when
• No plaintext keys: Credentials stay in the vault, not in config files

For security hardening details, check our OpenClaw Automation Pitfalls guide — many of the credential management pitfalls described there are now solved by this feature.

Discord and Telegram Session Improvements

Discord: Inactivity-Based Thread Lifecycle

Thread sessions now use inactivity timers instead of fixed TTL (time-to-live). This is a subtle but important change.

Old behavior: Thread session expires after X hours, regardless of activity. New behavior: Thread session expires after X hours of inactivity, with an optional hard maxAgeHours cap.

[channels.discord.threads]
idleHours = 24        # Expire after 24h of inactivity (default)
maxAgeHours = 168     # Hard cap at 7 days regardless of activity

New /session commands let users manage thread sessions directly within Discord:

• /session status — Check current session state
• /session reset — Clear session context
• /session extend — Extend session lifetime

Telegram: DM Topics

Telegram DM topics get first-class support with per-DM configuration:

[channels.telegram.dm]
requireTopic = true        # Force topic-based conversations
dmPolicy = "allowlist"     # Only approved senders

[channels.telegram.dm.topics.research]
skills = ["web_search", "web_fetch"]
systemPrompt = "You are a research assistant."

[channels.telegram.dm.topics.coding]
skills = ["exec", "browser"]
systemPrompt = "You are a coding assistant."

Each topic gets its own session, skills, and system prompt — essentially creating mini-agents within a single Telegram DM.

Android Device Integration

OpenClaw 2026.3.1 adds significant Android capabilities, turning your phone into a first-class agent endpoint:

These aren’t just read-only queries — you can build agents that actively manage your Android device. Imagine an agent that:

1. Checks your calendar for free slots
2. Reads your step count
3. Suggests a walking meeting and adds it to your calendar
4. Sends a WhatsApp message to the attendee

All automated through a single OpenClaw prompt.

Visual Diffs Plugin

A new diffs plugin provides read-only diff rendering with canvas/PNG output. This is designed for code review workflows where an AI agent can:

1. Detect code changes in a PR
2. Render a visual diff with syntax highlighting
3. Overlay its analysis and suggestions
4. Share the annotated diff in a messaging channel

This integrates naturally with CI/CD pipelines and team chat workflows.

How to Update

macOS / Linux

curl -fsSL https://openclaw.ai/install.sh | bash

Windows (PowerShell)

iwr -useb https://openclaw.ai/install.ps1 | iex

Docker

docker pull openclaw/openclaw:2026.3.1
# or use 'latest' for the most recent stable
docker pull openclaw/openclaw:latest

Verify the Update

openclaw --version
# Expected: openclaw 2026.3.1

# Check gateway health
openclaw gateway status

Post-Update Checklist

After updating, verify these items:

• Gateway starts without errors: openclaw gateway status
• Existing agent bindings are preserved: openclaw agents bindings
• Messaging channels are connected: openclaw channels list
• Health endpoints respond: curl http://127.0.0.1:18789/healthz
• External secrets (if configured): openclaw secrets audit

Breaking Changes and Migration Notes

WebSocket Transport Default

If your infrastructure doesn’t support WebSocket connections, you’ll need to explicitly set SSE:

[response]
transport = "sse"

This is the only change that might break existing setups. Everything else is backward-compatible.

Claude 4.6 Adaptive Thinking

If you were relying on consistent token usage for Claude 4.6 models, adaptive thinking might cause variability. Set mode = "low" for agents where you need predictable costs:

[agents.budget-conscious.model.thinking]
mode = "low"

Thread Session Lifecycle

Discord thread sessions now persist longer (until inactivity timeout) rather than expiring at a fixed time. If you rely on sessions expiring at predictable times, set a maxAgeHours value.

FAQ

What’s new in OpenClaw 2026.3.1?

The headline features are WebSocket-first transport for OpenAI models (lower latency), Claude 4.6 adaptive thinking (smarter reasoning), native Kubernetes health endpoints (production deployments), agent routing CLI (multi-agent management), and external secrets management (better security). The release also adds Android device capabilities and improved Discord/Telegram session handling.

How do I update to OpenClaw 2026.3.1?

Run curl -fsSL https://openclaw.ai/install.sh | bash on macOS/Linux or iwr -useb https://openclaw.ai/install.ps1 | iex on Windows. Docker users should pull openclaw/openclaw:2026.3.1. After updating, verify with openclaw --version and openclaw gateway status.

Does this release break anything?

The main potential breaking change is WebSocket becoming the default transport. If your network blocks WebSocket connections, set transport = "sse" in your config. Everything else is backward-compatible.

Should I upgrade right away?

If you’re running in production, yes — the Kubernetes health endpoints and external secrets management alone are worth the upgrade. The WebSocket transport also provides noticeable latency improvements. Test in a staging environment first, especially if you use a reverse proxy.

How does adaptive thinking affect my costs?

Adaptive thinking may increase token usage for complex queries (deeper reasoning) but decrease it for simple ones (shorter responses). On average, most users see similar or slightly lower costs because simple queries — which are the majority — use fewer tokens.

Related Reading

• OpenClaw Multi-Agent Guide — Set up multiple specialized agents on one instance
• OpenClaw Automation Pitfalls — Avoid common mistakes when automating with OpenClaw
• OpenClaw Architecture Deep Dive — Understand the gateway, agents, and plugin system
• OpenClaw Usage Tutorial — Getting started from scratch
• MCP Security Guide — Secure your AI agent integrations
• Claude Code Pricing 2026 — Compare Claude API costs for your OpenClaw agents

Based on OpenClaw 2026.3.1 release notes (March 2, 2026). For the full changelog, see the official GitHub releases page.