What can you do with this server?

The Strava MCP Server enables interaction with the Strava API to retrieve and manage user activities and segments: * Retrieve User Activities: Fetch activities for the authenticated user with optional filters for time range and pagination * Get Activity Details: Obtain detailed information about a specific activity, including options to include segment efforts * Retrieve Activity Segments: Access segments associated with a specific activity * Get Segment Leaderboard: View leaderboards for specific segments with various filtering options (gender, age group) * Authentication Management: Automatically handle Strava OAuth authentication, including token refresh and storage

Which integrations are available for this server?

Provides tools for accessing data from the Strava API, including retrieving user activities, getting specific activity details, accessing activity segments, and viewing segment leaderboards.

How do I use Strava MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Strava MCP Server show my last 5 running activities" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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Strava MCP Server

by yorrickjansen

Overview Schema Source Related Servers Score Discussions Admin

Python

Local

Strava MCP Server

CI/CD Pipeline codecov

A Model Context Protocol (MCP) server for interacting with the Strava API.

User Guide

Installation

You can easily install Strava MCP with uvx:

uvx strava-mcp

Setting Up Strava Credentials

Create a Strava API Application:
- Go to https://www.strava.com/settings/api
- Create a new application to obtain your Client ID and Client Secret
- For "Authorization Callback Domain", enter localhost

Configure Your Credentials: Create a credentials file (e.g., ~/.ssh/strava.sh):

export STRAVA_CLIENT_ID=your_client_id
export STRAVA_CLIENT_SECRET=your_client_secret

Configure Claude Desktop: Add the following to your Claude configuration (/Users/<username>/Library/Application Support/Claude/claude_desktop_config.json):
```
"strava": {
    "command": "bash",
    "args": [
        "-c",
        "source ~/.ssh/strava.sh && uvx strava-mcp"
    ]
}
```

Authentication

The first time you use the Strava MCP tools:

An authentication flow will automatically start
Your browser will open to the Strava authorization page
After authorizing, you'll be redirected back to a local page
Your refresh token will be saved automatically for future use

Available Tools

Get User Activities

Retrieves activities for the authenticated user.

Parameters:

before (optional): Epoch timestamp for filtering
after (optional): Epoch timestamp for filtering
page (optional): Page number (default: 1)
per_page (optional): Number of items per page (default: 30)

Get Activity

Gets detailed information about a specific activity.

Parameters:

activity_id: The ID of the activity
include_all_efforts (optional): Include segment efforts (default: false)

Get Activity Segments

Retrieves segments from a specific activity.

Parameters:

activity_id: The ID of the activity

Get Segment Leaderboard

Gets the leaderboard for a specific segment.

Parameters:

segment_id: The ID of the segment
Various optional filters (gender, age group, etc.)

Related MCP server: Strava MCP Server

Developer Guide

Project Setup

Clone the repository:
```
git clone <repository-url>
cd strava
```
Install dependencies:
```
uv install
```

Set up environment variables:

export STRAVA_CLIENT_ID=your_client_id
export STRAVA_CLIENT_SECRET=your_client_secret

Alternatively, create a .env file with these variables.

Running in Development Mode

Run the server with MCP CLI:

mcp dev strava_mcp/main.py

Manual Authentication

You can get a refresh token manually by running:

python get_token.py

Project Structure

strava_mcp/: Main package directory
- __init__.py: Package initialization
- config.py: Configuration settings using pydantic-settings
- models.py: Pydantic models for Strava API entities
- api.py: Low-level API client for Strava
- auth.py: Strava OAuth authentication implementation
- oauth_server.py: Standalone OAuth server implementation
- service.py: Service layer for business logic
- server.py: MCP server implementation
tests/: Unit tests
strava_mcp/main.py: Main entry point to run the server
get_token.py: Utility script to get a refresh token manually

Running Tests

pytest

Publishing to PyPI

Building the package

# Build both sdist and wheel
uv build

Publishing to PyPI

# Publish to Test PyPI first
uv publish --index testpypi

# Publish to PyPI
uv publish

License

MIT License

Acknowledgements

Available Tools

3 tools

get_activityC

Get details of a specific activity.

Args: ctx: The MCP request context activity_id: The ID of the activity include_all_efforts: Whether to include all segment efforts

Returns: The activity details

ParametersJSON Schema

Name	Required	Description	Default
`activity_id`	Yes
`include_all_efforts`	No

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get details' but doesn't clarify if this is a read-only operation, what permissions might be required, error handling, or response format beyond 'The activity details.' For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with a clear purpose statement followed by Args and Returns sections, making it easy to parse. It's concise with no wasted words, though the Args section could be more integrated into the main text for better flow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (2 parameters, no output schema, no annotations), the description is incomplete. It lacks details on error cases, authentication needs, rate limits, or what 'activity details' include, which are crucial for proper tool invocation. Without annotations or output schema, the description should provide more context to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal semantics beyond the input schema. It explains that 'activity_id' is 'The ID of the activity' and 'include_all_efforts' is 'Whether to include all segment efforts,' which clarifies purpose but doesn't provide format details or examples. With 0% schema description coverage, this partially compensates but remains basic, aligning with the baseline expectation when schema coverage is low.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get details of a specific activity.' This is a specific verb ('Get') and resource ('activity'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_activity_segments' or 'get_user_activities', which likely retrieve related but different data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_activity_segments' (which might retrieve parts of an activity) or 'get_user_activities' (which might list multiple activities), leaving the agent to infer usage context without explicit direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_activity_segmentsC

Get the segments of a specific activity.

Args: ctx: The MCP request context activity_id: The ID of the activity

Returns: List of segment efforts for the activity

ParametersJSON Schema

Name	Required	Description	Default
`activity_id`	Yes

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get[s] the segments' and returns a 'List of segment efforts for the activity', which implies a read-only operation, but it doesn't disclose any behavioral traits such as authentication needs, rate limits, error handling, or what 'segment efforts' entail. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with the main purpose stated first ('Get the segments of a specific activity.'). The Args and Returns sections are structured but could be more integrated. It avoids unnecessary fluff, but the separation into sections might slightly reduce flow. Overall, it's efficient with little waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (a read operation with one parameter) and lack of annotations or output schema, the description is incomplete. It doesn't explain what 'segment efforts' are, how the list is structured, or any behavioral aspects like pagination or errors. For a tool with no structured data support, the description should provide more context to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal meaning beyond the input schema. It mentions 'activity_id: The ID of the activity', which is already clear from the schema's title 'Activity Id' and type 'integer'. With 0% schema description coverage, the description doesn't compensate by providing additional context, such as where to find the activity ID or format requirements. However, since there's only one parameter, the baseline is higher, but it still lacks enrichment.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get the segments of a specific activity.' It uses a specific verb ('Get') and resource ('segments of a specific activity'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this from sibling tools like 'get_activity' or 'get_user_activities' in terms of what specific data it returns versus those tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_activity' or 'get_user_activities', nor does it specify prerequisites, exclusions, or contextual cues for choosing this tool over others. The only implied usage is when you need segments for a specific activity, but this is basic and lacks comparative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_user_activitiesB

Get the authenticated user's activities.

Args: ctx: The MCP request context before: An epoch timestamp for filtering activities before a certain time after: An epoch timestamp for filtering activities after a certain time page: Page number per_page: Number of items per page

Returns: List of activities

ParametersJSON Schema

Name	Required	Description	Default
`before`	No
`after`	No
`page`	No
`per_page`	No

TDQS

B3.2/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that it returns a 'List of activities' and includes pagination parameters, which hints at a read-only operation. However, it lacks details on authentication requirements, rate limits, error handling, or what constitutes an 'activity' (e.g., format, fields). This leaves significant gaps for an agent to understand the tool's behavior fully.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized. It starts with a clear purpose statement, followed by organized sections for 'Args' and 'Returns'. Each sentence adds value without redundancy, making it easy to parse and understand quickly. There's no wasted verbiage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (4 parameters, no annotations, no output schema), the description is moderately complete. It covers the purpose and parameters but lacks details on authentication, error cases, sibling differentiation, and the structure of returned activities. Without an output schema, the agent must infer the return format from the vague 'List of activities'. This is adequate but has clear gaps for a tool with multiple parameters and siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, but the description compensates by listing all four parameters ('before', 'after', 'page', 'per_page') with brief explanations in the 'Args' section. It clarifies that 'before' and 'after' are epoch timestamps for filtering, and 'page' and 'per_page' handle pagination. This adds meaningful context beyond the bare schema, though it doesn't detail defaults or constraints like valid ranges.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get the authenticated user's activities.' It specifies the verb ('Get') and resource ('authenticated user's activities'), making it clear what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_activity' or 'get_activity_segments', which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus its siblings ('get_activity' and 'get_activity_segments'). It doesn't mention any prerequisites, exclusions, or alternative scenarios. The only implied usage is for retrieving the user's activities, but this is too vague for effective tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

3 tool updatesMar 25, 2025
- First observedget_activity
- First observedget_activity_segments
- First observedget_user_activities

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

B3.1/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: get_activity retrieves details of a specific activity, get_activity_segments focuses on segments within an activity, and get_user_activities lists the user's activities. The descriptions clearly differentiate these functions, making tool selection unambiguous for an agent.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (get_activity, get_activity_segments, get_user_activities). The naming is predictable and readable, using 'get' as the verb throughout, which aligns well with the read-only nature of these tools.

Tool Count2/5

With only 3 tools, this server feels under-scoped for a Strava integration, which typically involves activities, segments, athletes, and more. While the tools cover some read operations, the count is too low to support comprehensive agent workflows, such as creating or updating activities, which are common in fitness tracking domains.

Completeness2/5

The tool surface is severely incomplete for a Strava server, as it only includes read operations (get) with no support for create, update, or delete actions. There are significant gaps, such as missing tools for managing segments, athletes, or uploading activities, which will likely cause agent failures when attempting full interactions with the Strava API.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

Reddit Discussion

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Looking for Admin?

If you are the server author, to access and configure the admin panel.

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