It’s 7:15 am. You just finished your morning run. You’re standing on the porch, cooling down, still breathing hard, and you open Telegram. Not to check messages. To ask your agent: “How was that run?”
Three seconds later, you get a summary. Pace compared to last week’s runs on the same route. Heart rate zones. Segment performance. A note that your easy runs are drifting too fast — maybe dial it back 15 seconds per mile.
That’s what OpenClaw Strava integration looks like in 2026. You don’t open the Strava app and scroll through metrics. You ask your AI agent what happened, and it reads your training data for you. Natural language questions, conversational answers, delivered through whichever messaging app you already use.
Why Athletes Are Connecting OpenClaw to Strava
Most runners and cyclists already use Strava. It tracks every workout, stores years of training history, and serves as a social network for athletes. So why route it through an AI agent?
Three reasons.
Faster access to insights. After a run, you want to know if you hit your target pace or if your heart rate stayed in zone 2. Opening Strava, navigating to the activity, and scanning the graphs takes 30 seconds. Asking your agent takes 5 seconds and gets you the answer in plain English.
Contextual training advice. Strava shows you data. An AI agent powered by Claude can interpret it. Compare today’s workout to last week, flag trends, suggest adjustments. “Your long runs are getting faster, but recovery pace is creeping up too. Try slowing down on easy days.”
Integration with your workflow. Your agent already manages your calendar, tasks, and reminders. Adding Strava means your training data sits next to everything else. Check your schedule for the week and get a reminder that you haven’t done a long run in ten days. Log a workout and have it automatically note the mileage in your habit tracker.
The OpenClaw framework has 145K+ GitHub stars and supports agents like Moltbot and Clawdbot. It’s open-source, MIT-licensed, and built for extensibility. Strava is one use case. Fitness tracking through chat is the broader pattern.
If you’re new to the ecosystem, our install guide covers setup from scratch. For more on how skills work, check the getting started tutorial. The Fitness category lists all curated health and training skills.
A Runner’s Morning: Before and After
Let’s walk through what Monday morning looks like for a runner named Maya. She trains five days a week, mixes intervals with easy runs, and is three months into marathon prep.
Before: The Strava App Workflow
Maya wakes up at 6:00 am. She does a 10K easy run, finishes around 6:50, and uploads the activity from her Garmin watch. By the time she’s inside, the run is synced to Strava.
Now she wants to check a few things:
- Did she stay in zone 2 the whole time? (This was supposed to be an easy run.)
- How does this pace compare to last Monday’s run?
- Is she on track for her weekly mileage goal?
She opens the Strava app, taps the activity, scrolls to the heart rate graph, and confirms she spiked into zone 3 for about 8 minutes. Then she goes back to her profile, finds last week’s Monday run, compares the paces manually, and does some mental math on her weekly mileage so far.
Five minutes, three screens, and a lot of tapping.
After: The OpenClaw Strava Workflow
Maya finishes her run. The activity auto-uploads to Strava. She opens Telegram while still standing on the porch and types:
“How was that run?”
Her agent replies:
10.2K in 58:14. Average pace 9:18/mile, about 10 seconds faster than last Monday. Heart rate stayed in zone 2 except for a spike around mile 6 (probably that hill on Oak Street). You’re at 24 miles this week with your long run still scheduled for Saturday. On track for 45.
One message. One response. She knows everything she needs to know.
Later in the day, she’s at her desk and wonders if she’s recovered enough for tomorrow’s interval session. She asks her agent:
“Show me my training load this week.”
The agent pulls her recent workouts, checks her mileage ramp, and flags that she ran five days in a row without a rest day. It suggests pushing tomorrow’s intervals to Wednesday.
She listens. Adjusts her calendar. Avoids overtraining.
What OpenClaw Strava Skills Can Do
There are a few Strava skills in the OpenClaw ecosystem. The most complete one is strava-connect, which handles the full OAuth flow and supports most of the Strava API.
Here’s what you get once it’s installed and connected:
Activity Summaries
Pull your most recent activity with pace, distance, elevation, heart rate data, and segment performance. Ask for specific runs by date or route name. Compare metrics across multiple activities.
Example: “Show me my last three long runs and compare average paces.”
Segment Tracking
Strava segments are one of the platform’s best features. Local climbs, sprint sections, popular loops — every athlete has a few segments they care about. The skill pulls segment times, shows your personal record, and compares your latest effort to past attempts.
Example: “Did I PR on the River Trail segment this morning?”
Training Load and Mileage
Check weekly mileage, monthly totals, and training load trends. The agent can calculate your mileage ramp rate and warn you if you’re increasing volume too fast (the classic recipe for injury).
Example: “What’s my mileage this month compared to last month?”
Social Features
Strava is part training log, part social network. The skill can pull recent activities from athletes you follow, show kudos on your runs, and post comments on friends’ workouts — all from chat.
Example: “Who in my club ran a marathon this weekend?”
Workout Planning
Ask your agent to suggest a workout based on your recent training. It reads your history, checks your mileage, and proposes an interval session or long run that fits your schedule.
Example: “I have an hour Wednesday morning. What workout should I do?”
A Cyclist’s Saturday: Chasing Segments
Let’s look at a different scenario. Daniel is a cyclist. He doesn’t race, but he cares about local segments. There are five climbs within riding distance of his house, and he’s been chasing top-10 finishes on all of them.
Saturday morning, he heads out for a 50-mile loop. The route hits three of his target segments. He pushes hard on each climb, legs burning, hoping to beat his previous times.
Back home, he wants to know immediately: Did he break into the top 10 on any of them?
He opens WhatsApp and asks his agent:
“How did I do on the segments today?”
The agent pulls his latest ride, identifies the three segments, and replies:
Segment 1 (Mt. Hamilton): 18:42. That’s your second-fastest time. Moved up to 12th place overall.
Segment 2 (Old La Honda): 19:05. PR by 8 seconds. You’re now 9th overall.
Segment 3 (Montebello): 21:30. Slower than usual, probably tired from the first two climbs.
He reads this while still clipped into his pedals. One question, instant feedback. He knows exactly where he stands.
Later, he checks the leaderboard for Old La Honda. His agent shows him the top 10 times. He’s 14 seconds behind 8th place. Doable. He marks it on his calendar for next Saturday.
Setting Up OpenClaw Strava Integration
Getting this working takes about 15 minutes. Most of that is OAuth setup, which is a one-time thing.
Install the Skill
First, make sure you have an OpenClaw agent running. If you’re starting from scratch, our getting started guide walks through agent setup and skill installation basics.
Once your agent is running, install the Strava skill:
clawhub install strava-connectVerify it’s loaded:
openclaw skills listYou should see strava-connect in the output.
Connect Your Strava Account
The skill uses OAuth to connect to your Strava account. You’ll need to authorize it once.
Send your agent a message:
Connect my Strava account.It will reply with a link. Click it, log into Strava, and approve access. The authorization covers activity data (read and write), segment data, and social features like kudos and comments.
Once authorized, your agent can pull any activity, segment, or training data from your Strava account.
Test It
Try a simple query to confirm everything works:
Show me my last run.The agent should return your most recent Strava activity with pace, distance, and any other metrics Strava recorded.
If you get an error, check that you completed the OAuth flow. Most issues come from incomplete authorization or expired tokens (which the skill should handle automatically, but sometimes don’t).
Real Training Scenarios
The setup is straightforward. The value shows up in day-to-day training. Here are three scenarios where athletes told us OpenClaw Strava integration made a real difference.
Scenario 1: The Morning Check-In
You run before work. You’re training for a half marathon, following a plan that alternates easy runs, tempo runs, and intervals. Every morning, you want to confirm you hit the right workout.
Instead of opening Strava and interpreting graphs, you ask your agent:
“Did I hit my target pace today?”
The agent reads your planned workout from your calendar (if you’ve set it up with cal-com or lark-calendar), compares it to your actual run, and tells you yes or no.
If you missed the target, it suggests adjustments. “You were 20 seconds per mile too fast. This was supposed to be an easy day. Try slowing down next time.”
That kind of feedback loop, delivered immediately after each run, keeps you on track without thinking too hard about the data.
Scenario 2: The Segment Hunter
You care about one specific segment. A local climb. You’ve been stuck in 15th place for three months. You want to break into the top 10.
Every time you ride that segment, you ask your agent:
“Did I PR on Hawk Hill?”
If yes, it tells you your new time and updated rank. If no, it tells you how far off you were and shows your best time for comparison.
You don’t need to navigate to the segment page, find your name on the leaderboard, and scroll through times. The answer comes to you instantly.
Over weeks, this creates a tight feedback loop. Attempt, check, adjust, repeat. That’s how you climb leaderboards.
Scenario 3: The Training Plan Review
Sunday evening. You’re planning the week ahead. You want to know if you’re on track with your training plan or if you need to adjust.
You ask your agent:
“Summarize my training this week.”
It pulls your runs, calculates total mileage, checks your workout distribution (easy vs. hard days), and compares it to the previous week. Then it suggests what next week should look like based on your mileage ramp and recovery status.
“You ran 38 miles this week, up from 34 last week. That’s about a 12% increase, which is safe. You had two hard workouts and four easy runs. Good balance. Next week, aim for 40-42 miles with one interval session and one tempo run.”
That kind of summary used to require a spreadsheet or a coach. Now it’s a single question in a chat window.
Combining Strava with Other Fitness Skills
OpenClaw Strava integration works well on its own. It works even better when combined with other fitness and productivity skills.
Habit Tracking
Use habit-tracker to log workouts and track streaks. When you finish a run, your agent can pull the data from Strava and automatically log it as a completed habit. No manual entry.
Example: “Log today’s run as a completed habit.”
Calendar Integration
Sync your planned workouts with cal-com or lark-calendar. Your agent knows what workout you planned for today, pulls your actual Strava data, and compares the two. Did you hit your target? Were you too fast or too slow?
Example: “Compare today’s run to what was on my calendar.”
Morning Briefing
Use mission-control to get a daily summary that includes your training status alongside tasks and calendar events. Start every morning with a full picture: meetings scheduled, tasks due, and whether you’re on track with your weekly mileage.
Example: “Give me my morning briefing.”
Workflow Automation
Use flowmind to chain actions together. Build a post-run flow that pulls your latest Strava activity, logs it as a habit, checks your weekly mileage, and updates your training plan. Trigger the whole sequence with a single command.
Example: “Run my post-workout flow.”
What OpenClaw Strava Can’t Do (Yet)
It’s worth being clear about the limitations. The integration is useful, but it’s not a full replacement for the Strava app.
No route planning. You can’t create or edit routes through the skill. Strava’s route builder is still the best tool for planning new rides or runs.
Limited social features. You can view recent activities from athletes you follow and post kudos or comments, but the full social feed experience doesn’t translate well to a chat interface. Browsing photos and reading long captions is better in the app.
No activity editing. You can’t crop activities, change titles, or fix GPS errors through the skill. For post-activity cleanup, you still need the Strava app or website.
Delayed data. Activity data syncs to Strava first, then your agent pulls it. There’s usually a 10-30 second delay between finishing a workout and being able to query it. Not a dealbreaker, but not instant either.
No live tracking. The skill reads completed activities. It can’t pull live data from a workout in progress. If you want real-time pace or heart rate, you need your watch or the Strava app.
None of these are blockers. The skill does what it’s built for: quick post-workout analysis and training data queries through chat. For everything else, the Strava app still exists.
FAQ
Does this work with cycling and running, or just one?
Both. The skill pulls all activity types from Strava. Running, cycling, swimming, hiking, skiing — if Strava tracks it, the skill can read it. Most examples in this article focus on running and cycling because those are the most common use cases, but the underlying functionality works for any sport.
Can I post activities to Strava through OpenClaw?
Yes, if you create the activity data manually. The skill supports uploading activities via the Strava API. But most athletes use a GPS watch or bike computer that auto-syncs to Strava, which is simpler. The skill is better for reading and analyzing data than for creating it.
Does this work with Garmin or Apple Watch data?
Indirectly. If your watch syncs to Strava, the skill can read the data once it’s there. OpenClaw doesn’t pull directly from Garmin Connect or Apple Health. Strava is the bridge.
How does the skill handle private activities?
Private activities are included in your data. The skill respects your Strava privacy settings. If an activity is marked private, only you (through your agent) can see it. Public activities are visible to anyone who follows you, just like on Strava.
Can multiple people share one OpenClaw agent for team training?
Technically yes, but it’s not ideal. Each agent connects to one Strava account. If you want multiple athletes using OpenClaw for training, each should run their own agent. That way, everyone gets personalized data and advice.
Is there a cost to use the Strava skill?
The skill is free and open source. OpenClaw is MIT-licensed. Strava itself is free for most features, with an optional premium subscription for advanced analytics. The skill works with both free and premium Strava accounts.
Clawdbot Strava: What Changed in 2026?
If you’ve been in the OpenClaw ecosystem for a while, you might remember the Clawdbot agent and its Strava integration from 2025. What’s different in 2026?
Not much in functionality, but the naming and ecosystem matured. Clawdbot is now called Moltbot, and the agent framework consolidated around OpenClaw as the core project. The Strava skill works the same way — OAuth connection, natural language queries, training data analysis.
The skill itself got more stable. Early versions had issues with expired tokens and inconsistent segment data. As of February 2026, those bugs are fixed. The developer ships regular updates, and the skill works reliably with both free and premium Strava accounts.
If you were using Clawdbot Strava in 2025, the migration to Moltbot is straightforward. The skill naming changed slightly (strava-connect instead of clawdbot-strava), but the commands and OAuth flow are identical.
Next Steps
New to OpenClaw? Start with our getting started guide. It covers agent setup, skill installation, and basic troubleshooting.
Already running an agent? Install the Strava skill and try a few queries after your next workout. The feedback loop is fast enough that you’ll notice the difference within a week.
Want to see what else athletes are building with OpenClaw? Browse the Fitness category for more health and training skills. Check the Productivity category for tools that pair well with training data, like habit trackers and calendar sync.
Oh My OpenClaw curates 433 skills across 10 categories. Strava integration is one piece. The broader pattern is this: connect your tools to an AI agent, interact through chat, and let Claude interpret the data for you. Start with fitness tracking. Expand from there.