How do I export a route to my GPS device?

First, use list_routes to find your route ID. Then use export_route_gpx or export_route_tcx with that route ID. The GPX file can be downloaded and loaded onto Garmin, Wahoo, or other GPS devices for turn-by-turn navigation during your workout.

Can I log activities that Strava doesn't automatically track?

Yes! Use create_activity to manually log any workout — gym sessions, yoga, swimming, hiking, cross-training. Provide the name, type (e.g., "Workout", "Yoga", "Swim"), start date, elapsed time, and optionally distance and description. This keeps all your training in one place.

How do I track my bike and shoe mileage?

Use get_gear with the gear ID to see total accumulated distance. Gear IDs are found in your athlete profile or assigned to activities. You can assign gear to activities using update_activity with the gear_id parameter. Track mileage to know when to replace chains, tires, or running shoes.

Strava Planning MCP Server for CrewAI 14 tools — connect in under 2 minutes

Name: Strava Planning
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 14 Tools Framework

Connect your CrewAI agents to Strava Planning through Vinkius, pass the Edge URL in the `mcps` parameter and every Strava Planning tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Strava Planning Specialist",
    goal="Help users interact with Strava Planning effectively",
    backstory=(
        "You are an expert at leveraging Strava Planning tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Strava Planning "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 14 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Strava Planning MCP Server

Connect Strava Planning to any AI agent and manage your training logistics — route creation, GPX/TCX export, manual activity logging, gear tracking, segment favoriting, and profile management.

When paired with CrewAI, Strava Planning becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Strava Planning tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Route Management — List, view, and analyze all your saved routes with distance, elevation, and descriptions
Route Streams — Get GPS coordinates, elevation profiles, and distance data for any route
Route Export — Export routes to GPX and TCX formats for GPS devices (Garmin, Wahoo, etc.)
Manual Activity Creation — Log activities not recorded by Strava (gym, yoga, cross-training) with full details
Activity Updates — Edit activity names, descriptions, assign gear, mark commutes or indoor sessions
File Uploads — Upload FIT, TCX, or GPX files for processing by Strava with status tracking
Segment Management — Star (favorite) or unstar segments for quick training access
Athlete Profile — View and update your profile information including weight for accurate power-to-weight ratios
Athlete Zones — Review your heart rate and power zone configurations
Gear Details — Track equipment mileage, models, and primary gear assignments

The Strava Planning MCP Server exposes 14 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Strava Planning to CrewAI via MCP

Follow these steps to integrate the Strava Planning MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 14 tools from Strava Planning

Why Use CrewAI with the Strava Planning MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Strava Planning through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Strava Planning + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Strava Planning MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Strava Planning for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Strava Planning, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Strava Planning tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Strava Planning against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Strava Planning MCP Tools for CrewAI (14)

These 14 tools become available when you connect Strava Planning to CrewAI via MCP:

create_activity

Required: name (activity name), type (activity type like "Run", "Ride", "Swim", "Walk", "Hike"), startDate (ISO 8601 format), elapsedTime (seconds). Optional: description, distance (meters). Use this to log activities recorded outside of Strava (gym workouts, yoga, cross-training, etc.). Activity types must match Strava's valid types list. Create a manual activity in Strava

export_route_gpx

GPX files can be downloaded and loaded onto GPS devices (Garmin, Wahoo, etc.) for navigation. The routeId is from Strava route URLs. Use this to export routes to your GPS device for guided training. Get the GPX export URL for a Strava route

export_route_tcx

TCX files include route data with additional training metadata. Compatible with Garmin Training Center and other fitness platforms. Use this to export routes with training metadata. Get the TCX export URL for a Strava route

get_athlete

Use this to review personal profile details, check equipment assignments, or verify account settings. Get the authenticated athlete's profile information

get_athlete_zones

Required for zone-based training analysis. Use this to review training zones, ensure zones are correctly set, or use zone data for activity analysis. Get the athlete's custom heart rate and power zones

get_gear

The gearId is found in activity data or athlete profile. Use this to check equipment mileage for maintenance planning or to analyze performance with specific gear. Get details about a piece of equipment (bike, shoes) tracked in Strava

get_route

The routeId is found in Strava route URLs. Use this to review route characteristics before training or to plan similar routes. Get detailed information about a specific Strava route

get_route_streams

The "types" parameter is comma-separated: "latlng", "altitude", "distance". Use this to preview a route's elevation profile, understand the terrain, or export GPS data for navigation. Get elevation and GPS data streams for a Strava route

get_upload_status

Status values: "Your activity is ready" (success), "Your activity is still processing" (wait and retry), or error messages. The uploadId is returned by upload_activity. Poll this endpoint every 5-10 seconds after upload until ready. Check the status of a Strava activity upload

list_routes

Each route includes: name, distance, elevation gain, type (ride/run), description, and whether it's private. Use this to review saved routes, plan upcoming workouts, or export route data for GPS devices. List all routes created by the authenticated athlete

star_segment

Set starred=true to favorite, starred=false to unfavorite. The segmentId is from Strava segment URLs. Use this to manage your favorite segments for quick access and training focus. Star (favorite) or unstar a Strava segment

update_activity

The activityId is the numeric ID. Updatable fields: name, description, sport_type, gear_id (to assign equipment), commute (mark as commute: "true"/"false"), trainer (mark as indoor: "true"/"false"). Use this to correct activity details, assign gear, or add descriptions after the fact. Update an existing Strava activity

update_athlete

Currently only "weight" (in kg) is supported by the API. Accurate weight is important for power-to-weight ratio calculations and performance analysis. Use this when your weight changes to keep performance metrics accurate. Update the authenticated athlete's profile information

upload_activity

Supported data_type: "fit", "fit.gz", "tcx", "tcx.gz", "gpx", "gpx.gz". Returns an upload ID to check status with get_upload_status. Note: Actual file upload requires multipart/form-data with the file content. This endpoint initiates the process. Check upload status periodically — processing takes 10-60 seconds. Upload an activity file (FIT, TCX, GPX) to Strava for processing

Example Prompts for Strava Planning in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Strava Planning immediately.

"List all my saved routes."

"Export route 12345 to GPX format."

"Create a manual activity for today's gym session."

Troubleshooting Strava Planning MCP Server with CrewAI

Common issues when connecting Strava Planning to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Strava Planning + CrewAI FAQ

Common questions about integrating Strava Planning MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.