2,500+ MCP servers ready to use
Vinkius

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

Built by Vinkius GDPR 14 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Strava Planning through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "strava-planning": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Strava Planning, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Strava Planning
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.

LangChain's ecosystem of 500+ components combines seamlessly with Strava Planning through native MCP adapters. Connect 14 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

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

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save the code and run python agent.py

04

Explore tools

The agent discovers 14 tools from Strava Planning via MCP

Why Use LangChain with the Strava Planning MCP Server

LangChain provides unique advantages when paired with Strava Planning through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine Strava Planning MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Strava Planning queries for multi-turn workflows

Strava Planning + LangChain Use Cases

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

01

RAG with live data: combine Strava Planning tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Strava Planning, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Strava Planning tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Strava Planning tool call, measure latency, and optimize your agent's performance

Strava Planning MCP Tools for LangChain (14)

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

01

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

02

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

03

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

04

get_athlete

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

05

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

06

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

07

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

08

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

09

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

10

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

11

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

12

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

13

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

14

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 LangChain

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

01

"List all my saved routes."

02

"Export route 12345 to GPX format."

03

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

Troubleshooting Strava Planning MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Strava Planning + LangChain FAQ

Common questions about integrating Strava Planning MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

Connect Strava Planning to LangChain

Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.