How to Connect OpenClaw to Slack in Under 5 Minutes

Why Bringing an AI Agent Into Slack Actually Matters

Most teams already live in Slack. Standups happen there. Incidents get triaged there. Product decisions get debated, forgotten, and rediscovered there. So when people talk about "adding AI to their workflow," the real question isn't whether to use an AI agent — it's whether that agent can meet your team where they already are.

That's exactly what SlackClaw is designed to do. It takes OpenClaw, the open-source AI agent framework, and runs it as a dedicated, persistent agent directly inside your Slack workspace. No tab-switching, no copy-pasting context, no asking your teammates to adopt yet another tool. The agent is already in the channel.

This guide walks you through the full setup process — from zero to a functioning autonomous agent — in under five minutes. We'll also cover how to point it at your real tools so it can do meaningful work on day one.

Before You Begin: What You'll Need

Setup is intentionally lightweight, but you'll want to have the following ready:

• A Slack workspace where you have admin privileges (or can request a Slack app installation)
• A SlackClaw account — you can sign up free at slackclaw.com
• OAuth credentials or login access for whichever tools you want to connect first (GitHub, Notion, Linear, etc.)

That's genuinely it. SlackClaw handles the infrastructure — your agent runs on a dedicated server provisioned specifically for your team, so you're not sharing compute or context with anyone else.

Step 1: Create Your SlackClaw Account and Workspace

Head to slackclaw.com and click Get Started. You'll be prompted to sign in with your Slack workspace — this is the same OAuth flow you've done a hundred times for other Slack apps.

1. Click Sign in with Slack and authorize SlackClaw to access your workspace.
2. Choose which Slack workspace you want to connect. If you manage multiple, pick the one where your team is most active.
3. SlackClaw will request a standard set of Slack permissions: the ability to read and post messages, join channels it's invited to, and access user info for context.
4. Once authorized, you'll land in the SlackClaw dashboard. Behind the scenes, your dedicated agent server is already being spun up — this typically takes about 30 seconds.

When your server is ready, you'll see a confirmation and a prompt to invite the SlackClaw bot to your first channel.

Step 2: Invite the Agent to a Channel

In Slack, navigate to the channel where you want the agent to live. A good starting point is a private #ai-agent channel or an existing #dev-tools channel where your team already experiments.

/invite @SlackClaw

Once invited, you can send a quick test message to confirm it's alive:

@SlackClaw what can you help me with?

You'll get a response listing the agent's current capabilities and any tools it's already connected to. At this point, the agent is running but not yet connected to your actual toolstack — that's Step 3.

Step 3: Connect Your Tools via One-Click OAuth

This is where SlackClaw earns its keep. From the dashboard, navigate to the Integrations tab. You'll see a searchable catalog of 800+ tools your agent can connect to. Learn more about our pricing page.

For most teams, the highest-value integrations to set up first are:

• GitHub — so the agent can open issues, review PRs, check CI status, and summarize recent commits
• Linear or Jira — for creating, updating, and querying tickets without leaving Slack
• Notion — so the agent can search your docs, create pages, and pull in relevant context
• Gmail or Outlook — for drafting emails, summarizing threads, and managing follow-ups
• Slack itself — yes, it can search message history, summarize threads, and act on channel activity

Connecting each one is a single button click followed by a standard OAuth consent screen. No API keys to copy, no webhook URLs to configure, no documentation to dig through. Click Connect, authorize the app, and the integration is live. Learn more about our integrations directory.

A Practical Example: Connecting GitHub

1. In the Integrations tab, search for GitHub.
2. Click Connect. You'll be redirected to GitHub's OAuth page.
3. Choose whether to grant access to all repositories or specific ones. For a first pass, scoping it to one or two active repos is perfectly fine.
4. Authorize and you're redirected back to the SlackClaw dashboard. GitHub now appears as a connected integration with a green status indicator.

Back in Slack, you can immediately test it:

@SlackClaw summarize the last 5 pull requests in acme-corp/backend

The agent will query GitHub directly and return a formatted summary — no copy-pasting URLs, no switching tabs.

Step 4: Understand Persistent Memory

One of the most underappreciated things about SlackClaw is that your agent actually remembers things. This isn't a stateless chatbot that forgets everything between sessions. Because your agent runs on a dedicated server, it maintains persistent memory and context across every conversation, every channel, and every team member who interacts with it.

In practice, this means:

• If you tell the agent your team follows a specific PR review process on Monday, it will apply that context when someone asks about PRs on Friday.
• If a teammate already asked the agent to track a Linear project, you don't have to re-explain the context when you ask a follow-up question a week later.
• The agent can build up a working model of your team's projects, preferences, and conventions over time — getting more useful the longer you use it.

Think of it less like a search engine and more like a new team member who's been quietly onboarding for weeks — reading your docs, watching your channels, and learning how your team actually operates.

You can explicitly feed the agent context too. From the dashboard, use the Memory tab to add standing instructions, project descriptions, or team preferences that persist across all sessions.

Step 5: Configure Custom Skills (Optional but Powerful)

OpenClaw's underlying framework is extensible, and SlackClaw exposes this through Custom Skills — pre-defined workflows you can trigger with natural language.

For example, you might create a skill called Weekly Standup Digest that:

1. Pulls merged PRs from GitHub for the past 7 days
2. Fetches completed tickets from Linear
3. Summarizes Slack threads in #engineering that had high activity
4. Posts a formatted digest to #standup every Monday at 9am

Skills are configured from the dashboard using a simple step-based editor — no code required for standard workflows. If you want to go deeper, SlackClaw also supports custom Python skill definitions that plug directly into the OpenClaw skill registry:

from openclaw.skills import skill

@skill(name="deploy_status", description="Check the current deploy status for a service")
def deploy_status(service_name: str) -> str:
    # Your custom logic here
    return f"Fetching deploy status for {service_name}..."

This is particularly useful for teams with internal APIs or proprietary systems that aren't in the standard integration catalog.

Understanding Credit-Based Pricing

SlackClaw uses a credit-based pricing model rather than per-seat licensing. This is a deliberate choice that reflects how AI agents actually get used — it's not one person running one query at a time. It's a whole team, asking questions at different volumes, running automated skills in the background, and occasionally kicking off heavy multi-step tasks. For related insights, see Connecting AWS CloudWatch Alerts to OpenClaw in Slack.

Per-seat pricing penalizes adoption. Credit pricing means you pay for what the agent actually does, not how many people have access to it. Invite your entire engineering team to the #ai-agent channel on day one — there's no financial reason not to.

Credits are consumed by agent actions: tool calls, LLM completions, and skill executions. Light conversational use costs very little. A complex multi-step task that queries GitHub, updates Linear tickets, drafts a Notion page, and posts a Slack summary will consume more — but it also just did the work of 20 minutes of manual effort.

What to Try First: High-Value Use Cases

Once you're set up, here are three workflows worth trying in your first week:

1. Incident Triage

Invite the agent to your #incidents channel. When something breaks, ask it to pull recent deploys from GitHub, check for related Linear issues, and draft an initial incident summary. What used to take 10 minutes of frantic tab-switching takes 30 seconds.

2. Async Standup Summaries

Ask the agent to summarize what each teammate worked on yesterday by pulling their GitHub commits, Linear ticket updates, and Slack messages. Useful for distributed teams across timezones who can't make a synchronous standup work.

3. Ticket Triage from Slack

Forward a customer complaint or bug report to the agent and ask it to create a Linear or Jira ticket with appropriate context, assign it to the right team member, and link any related GitHub issues. One message, fully triaged. For related insights, see Link Jira Projects to OpenClaw in Slack.

You're Ready

The whole point of SlackClaw is that your team shouldn't have to change how they work to benefit from an AI agent. The agent comes to Slack, connects to the tools you already use, remembers what matters, and gets out of the way until you need it.

Setup takes five minutes. The compounding value of a persistent, context-aware agent that knows your stack, your team, and your workflows — that builds over weeks and months. Start with one channel, connect two or three tools, and see what it does with real work before you decide how far to take it.