AI running coach powered by Strava data, science-backed training plans, and community challenges.
If you already use Coach Leo, the coach leo mcp server is the piece that lets your assistant work with it directly. AI running coach powered by Strava data, science-backed training plans, and community challenges.
An AI running coach that connects to your Strava, Suunto, or Polar data, builds plans from your real history, and adapts daily based on how you actually feel.
Coach Leo is a full AI running coach application at coachleo.ai. It connects to your Strava account, reads your real training history (pace, heart rate, elevation, cadence), and uses specialized coaching tools to make decisions — like a real coach with access to your training diary.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
get_coaching_briefing — Complete coaching context: profile, recent activities, training load, alerts, readiness, character statusathlete — Runner profile and running character management. Body metrics, preferences, character recalculationactivity — Query and annotate synced activities. Filter by date, sport, impact. Record feedbacktraining — Create and manage personalized training plans. Modify sessions, track adherencebody_signals — Log body observations, record physical setbacks, daily readiness check-insshoes — Track shoe collection, wear inspections across 6 zones, mileage stats, and retirementrace — Full race lifecycle: discovery via web search, registration, preparation, results, post-race analysisrace_performance — Race-time estimates and VO2max across distances from training data — trail-adjusted, tracked over timeknowledge — Hybrid semantic + full-text search across 200+ peer-reviewed papersmemory — Persistent memory across sessions. Logs decisions, prevents contradictory adviceget_skill_workflow — Loads a predefined coaching workflow that chains tools for a complex scenarioAuthentication — The Authentication tool exposed by this serverBecause this one is hosted, setup is mostly authentication — you point your client at the endpoint and approve access. Nothing runs on your machine, so there is no runtime to keep patched.
Plenty of knowledge and memory servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Coach Leo's toolset — get_coaching_briefing, athlete, activity and 9 more — is a fair guide to whether it matches your workflow. It is maintained by leo-runningcoach; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| get_coaching_briefing | Complete coaching context: profile, recent activities, training load, alerts, readiness, character status. |
| athlete | Runner profile and running character management. Body metrics, preferences, character recalculation. |
| activity | Query and annotate synced activities. Filter by date, sport, impact. Record feedback. |
| training | Create and manage personalized training plans. Modify sessions, track adherence. |
| body_signals | Log body observations, record physical setbacks, daily readiness check-ins. |
| shoes | Track shoe collection, wear inspections across 6 zones, mileage stats, and retirement. |
| race | Full race lifecycle: discovery via web search, registration, preparation, results, post-race analysis. |
| race_performance | Race-time estimates and VO2max across distances from training data — trail-adjusted, tracked over time. |
| knowledge | Hybrid semantic + full-text search across 200+ peer-reviewed papers. |
| memory | Persistent memory across sessions. Logs decisions, prevents contradictory advice. |
| get_skill_workflow | Loads a predefined coaching workflow that chains tools for a complex scenario. |
| Authentication | The Authentication tool exposed by this server. |
{
"mcpServers": {
"coach-leo": {
"url": "https://mcp.coachleo.ai/mcp"
}
}
}Configuration as documented by the project. Restart the client after saving.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.