Hevy MCP Server

Talk to your Hevy workout data from Claude, Cursor, Codex, and other MCP clients.

Connect to the hosted MCP · Use the read-only CLI · Watch the 18-second demo · Explore all 25 tools

Read-only CLI

Prefer the terminal? The separate @chrisdoc/hevy-cli package reads workouts, routines, exercises, and body measurements directly from the Hevy API. It never creates, updates, or deletes Hevy data.

npm install -g @chrisdoc/hevy-cli
export HEVY_API_KEY=your-hevy-api-key

hevy workouts list --page-size 10
hevy summary --weeks 4

Add --json to any command for scripts and pipelines. The CLI is a standalone Hevy API client, not an MCP wrapper. See packages/cli/README.md for the full command reference, pagination behavior, and exit codes.

hevy-mcp is an open-source Model Context Protocol (MCP) server for the Hevy fitness and workout tracking app. It lets AI assistants read, analyze, create, and update your Hevy workouts, routines, exercise templates, and body measurements through authenticated Hevy API requests.

The repository is organized as a private workspace with explicit runtime boundaries: @hevy-mcp/hevy-client owns the web-safe Hevy client, @hevy-mcp/core owns MCP tools and server construction, hevy-mcp is the published Node.js stdio adapter, and @hevy-mcp/worker is the private Cloudflare HTTP/OAuth adapter. Only the Node workspace is publishable.

A Hevy API key, available with Hevy PRO, is required.

See it in action

In the demo, the assistant retrieves real Hevy data and answers a multi-part training question with evidence from the user's workout history.

What can you do with it?

Analyze training progress: summarize 1-12 weeks of workouts and body measurements in one tool call.
Ask questions in plain language: find recent sessions, frequently trained exercises, consistency gaps, routine details, or exercise history.
Plan and log training: create or update workouts, routines, routine folders, custom exercises, and body measurements.
Search without huge responses: discover routines and exercise templates with compact, AI-friendly results.
Connect from your preferred MCP client: use the hosted Streamable HTTP endpoint or run locally with Codex, Claude Desktop, Cursor, and other clients.
Start without installing anything: connect directly to the production Cloudflare Worker—no Node.js, package download, or Docker container required.
Keep local control when you want it: run the same server with npx, bunx, or the official Docker image.

Try asking:

Analyze my training over the last six weeks. Show workouts per week, my most frequently trained exercises, any obvious gaps or inconsistencies, and cite the workout evidence you used.

Find my push-day routine and show its exercises and sets.

Compare my recent body measurements with my training consistency.

Create a completed workout from my saved routine. Ask me for any missing set results before writing it to Hevy.

Quick start

1. Get your Hevy API key

Create an API key in Hevy, then keep it somewhere secure. API access currently requires a Hevy PRO subscription.

2. Connect `hevy-mcp` to your client

The hosted Cloudflare endpoint is the fastest way to start. It runs remotely, so your client does not need Node.js, Bun, Docker, or a local server process.

Connect to the hosted endpoint

Production URL:

https://mcp.hevy-mcp.dev/mcp

The endpoint uses Streamable HTTP. Send your Hevy API key as a bearer token on every request.

Codex

Codex CLI, the Codex desktop app, and the IDE extension share the same MCP configuration. Make your Hevy API key available in the environment that starts Codex, then add the hosted server:

export HEVY_API_KEY=your-hevy-api-key
codex mcp add hevy \
  --url https://mcp.hevy-mcp.dev/mcp \
  --bearer-token-env-var HEVY_API_KEY

Codex stores the environment variable name, not the key itself, in its MCP configuration. Restart Codex or begin a new session, then run codex mcp list to verify the server is configured.

Other Streamable HTTP clients

Clients that accept a remote MCP URL and fixed headers commonly use this shape:

{
	"mcpServers": {
		"hevy": {
			"url": "https://mcp.hevy-mcp.dev/mcp",
			"headers": {
				"Authorization": "Bearer your-hevy-api-key"
			}
		}
	}
}

Exact configuration keys vary by client. The hosted server requires support for Streamable HTTP and a fixed Authorization header.

[!IMPORTANT] Treat the bearer value like a password. The Worker validates it with Hevy for each request, does not store it, and forwards it to Hevy only as the required api-key header.

Run locally instead

Choose local stdio if you prefer to run the server on your own machine or your client cannot attach a fixed authorization header to remote MCP requests.

Codex

codex mcp add hevy \
  --env HEVY_API_KEY=your-hevy-api-key \
  -- npx -y hevy-mcp

Claude Desktop or Cursor

Add this mcpServers entry to your client configuration:

{
	"mcpServers": {
		"hevy": {
			"command": "npx",
			"args": ["-y", "hevy-mcp"],
			"env": {
				"HEVY_API_KEY": "your-hevy-api-key"
			}
		}
	}
}

Google Antigravity

There are two ways to configure the Hevy MCP server for Google Antigravity (agy):

Option A: Automatic Plugin Installation (Recommended)

This utilizes the built-in plugin system:

Install the plugin:

agy plugin install https://github.com/chrisdoc/hevy-mcp

Provide the HEVY_API_KEY in your host shell environment so the CLI child process can inherit it:
- Persistent: Save the environment variable HEVY_API_KEY in your system/shell configurations:
  - macOS / Linux: Add it to your shell profile configurations (e.g., ~/.zshrc or ~/.bashrc):
```
export HEVY_API_KEY="your-actual-api-key"
```
  - Windows: Add it to your User or System Environment Variables. In PowerShell, you can run:
```
[Environment]::SetEnvironmentVariable("HEVY_API_KEY", "your-actual-api-key", "User")
```
- Temporary (Session-only): If you do not want to persist the key, export it in your active terminal session before running agy:
```
export HEVY_API_KEY="your-actual-api-key"
```

Option B: Manual Configuration (No Plugin)

If you prefer configuring it statically via the global configuration file:

Open your global MCP configuration file:
- Location: ~/.gemini/config/mcp_config.json
Add the hevy configuration block under the mcpServers key. Make sure to merge this entry with any existing servers you have configured rather than replacing the entire file contents:
```
{
	"mcpServers": {
		"hevy": {
			"command": "npx",
			"args": ["-y", "hevy-mcp"],
			"env": {
				"HEVY_API_KEY": "your-actual-api-key"
			}
		}
	}
}
```

Common local configuration locations:

Claude Desktop on macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Claude Desktop on Windows: %APPDATA%\Claude\claude_desktop_config.json
Cursor: ~/.cursor/mcp.json

Restart or reconnect the client after saving the file.

Any stdio MCP client

Configure your client to launch this command with HEVY_API_KEY in the child process environment:

npx -y hevy-mcp

npx requires Node.js 20 or newer. Restart or reconnect your client after saving its configuration.

Requires Bun:

{
	"mcpServers": {
		"hevy": {
			"command": "bunx",
			"args": ["hevy-mcp@latest"],
			"env": {
				"HEVY_API_KEY": "your-hevy-api-key"
			}
		}
	}
}

Official images support linux/amd64 and linux/arm64. Keep stdin open with -i because the container runs the stdio MCP server:

export HEVY_API_KEY=your-hevy-api-key
docker run -i --rm -e HEVY_API_KEY ghcr.io/chrisdoc/hevy-mcp:latest

For an MCP client, store the key in a protected environment file and configure the client to launch Docker:

{
	"mcpServers": {
		"hevy": {
			"command": "docker",
			"args": [
				"run",
				"-i",
				"--rm",
				"--env-file",
				"/absolute/path/to/hevy-mcp.env",
				"ghcr.io/chrisdoc/hevy-mcp:latest"
			]
		}
	}
}

Pin an exact image tag such as ghcr.io/chrisdoc/hevy-mcp:X.Y.Z when you need reproducible upgrades.

You can also add the npm server to supported clients with add-mcp:

npx add-mcp hevy-mcp --env "HEVY_API_KEY=your-hevy-api-key"

3. Ask your first question

Try one of these after restarting or reconnecting your MCP client:

“Give me a training summary for the last four weeks.”
“What routines do I have saved on Hevy?”
“Show my three most recent workouts.”
“Find exercise templates containing squat.”
“Which Hevy account is connected?”

Your assistant should ask for approval before mutation tools when the client supports tool confirmations.

How it works

Hosted:  Your AI assistant  →  Streamable HTTP  →  Cloudflare Worker  →  Hevy API
Local:   Your AI assistant  →  MCP over stdio   →  local hevy-mcp     →  Hevy API

The hosted endpoint creates a fresh MCP server and Hevy client for each request. It validates the supplied key with Hevy, keeps no shared user session, and does not persist the key. The local server follows the same tool contract but runs on your machine and receives the key through its child-process environment.

In either mode, read tools retrieve data; mutation tools create or replace data only when your assistant calls them.

Guided prompts

These server-provided MCP prompts coordinate common multi-step workflows:

Prompt	Arguments	Workflow
`analyze-workout-progress`	Optional `weeks` from 1-12; default `4`	Calls `get-training-summary`, then analyzes workout activity and body-measurement trends from the returned evidence.
`create-workout-from-routine`	Required `routineId` and UTC `startTime`	Loads a routine, collects actual completed-set data and an end time, then creates a workout without inventing results.

[!NOTE] With MCP SDK v1.29.0, clients invoking analyze-workout-progress with its default value must send arguments: {}. Omitting the entire arguments object is rejected by that SDK version before the default is applied.

Tools

hevy-mcp registers 25 tools. Read-only tools are safe for exploration; create and update tools are exposed with MCP mutation annotations so compatible clients can request confirmation.

Category	Tool	Description
Training analysis	`get-training-summary`	Summarize 1-12 weeks of workout activity and body-measurement trends in one call.
Workouts	`get-workouts`	List workouts from newest to oldest with exercise and timing details.
Workouts	`get-workout`	Get complete details for one workout by ID.
Workouts	`get-workout-count`	Return the account's total workout count.
Workouts	`get-workout-events`	List workout update and delete events since a timestamp.
Workouts	`create-workout`	Create a completed workout in Hevy.
Workouts	`update-workout`	Replace an existing workout by ID.
Routines	`search-routines`	Search routine titles and return compact metadata for discovery.
Routines	`get-routines`	List custom and default workout routines.
Routines	`get-routine`	Get one routine and its exercise configuration by ID.
Routines	`create-routine`	Create a reusable workout routine.
Routines	`update-routine`	Replace an existing routine's content.
Routine folders	`get-routine-folders`	List default and custom routine folders.
Routine folders	`get-routine-folder`	Get one routine folder's metadata by ID.
Routine folders	`create-routine-folder`	Create a routine folder.
Exercise templates	`get-exercise-templates`	List exercise templates with equipment and muscle metadata.
Exercise templates	`get-exercise-template`	Get complete metadata for one exercise template by ID.
Exercise templates	`search-exercise-templates`	Search the full exercise catalog by title substring.
Exercise templates	`create-exercise-template`	Create a custom exercise template.
Exercise history	`get-exercise-history`	Get past performed sets for one exercise template.
Body measurements	`get-body-measurements`	List dated body measurements.
Body measurements	`get-body-measurement`	Get the body measurement entry for one date.
Body measurements	`create-body-measurement`	Create a dated body measurement.
Body measurements	`update-body-measurement`	Update the body measurement for an existing date.
Account	`get-user-info`	Return the user's ID, display name, and public profile URL.

The Hevy API currently exposes no delete endpoints for workouts, routines, routine folders, exercise templates, or body measurements, so there are no corresponding delete tools.

Resources

Name	URI	Description
`user-profile`	`hevy://user`	Authenticated Hevy user profile.
`workout-count`	`hevy://workout-count`	Total number of workouts in the account.
`exercise-templates`	`hevy://exercise-templates`	Full formatted exercise template catalog.
`routine-folders`	`hevy://routine-folders`	Full formatted list of Hevy routine folders.

Hosted Cloudflare endpoint

The production MCP server is live at:

https://mcp.hevy-mcp.dev/mcp

It is the quickest way to use hevy-mcp: there is nothing to install or keep running locally, and it exposes the same 25 tools as the npm package and Docker image.

The Cloudflare Worker uses stateless Streamable HTTP at POST /mcp. Clients must send their Hevy API key as a fixed authorization header:

{
	"mcpServers": {
		"hevy": {
			"url": "https://mcp.hevy-mcp.dev/mcp",
			"headers": {
				"Authorization": "Bearer your-hevy-api-key"
			}
		}
	}
}

The bearer value is your Hevy API key, not an OAuth token. The Worker validates the key with Hevy on each request, does not store it, and forwards it upstream only as Hevy's required api-key header.

OAuth for Claude.ai and other remote MCP clients

Workers deployed with an OAUTH_KV namespace binding (see CONTRIBUTING.md) additionally expose a full OAuth 2.1 layer for clients that cannot send a fixed header, such as Claude.ai custom connectors:

RFC 8414 / RFC 9728 discovery metadata under /.well-known/
Dynamic client registration (/register) and PKCE token exchange (/token)
An /authorize page where you paste your Hevy API key once; the key is validated with Hevy and stored encrypted inside the OAuth grant

Add the Worker URL ending in /mcp as a Claude.ai custom connector and complete the authorization flow in the browser. Direct Authorization: Bearer <hevy-api-key> requests keep working unchanged — the OAuth layer is purely additive — and rotating your Hevy API key invalidates every OAuth grant created with it.

The endpoint does not expose legacy SSE or a GET event stream. Without the opt-in OAuth layer, clients that require OAuth discovery, dynamic registration, or token refresh are not compatible unless they can send the fixed custom header above.

Self-host the Worker

See CONTRIBUTING.md to deploy the Cloudflare Worker for self-hosted Streamable HTTP.

Advanced configuration

Setting	Default	Scope	Notes
`HEVY_API_KEY`	None; required	Local stdio or HTTP	Hevy API key from the Hevy app. Never pass it in a URL.
`HEVY_MCP_API_TIMEOUT`	`30000` ms	Local stdio	Positive Hevy API timeout in milliseconds. Invalid values fall back to 30 seconds.
`HEVY_MCP_DEBUG`	Disabled	Local Node	Set to exactly `1` for privacy-bounded diagnostics on stderr. Stdout remains reserved for MCP JSON-RPC.
`HEVY_MCP_HTTP_BEARER_TOKEN`	None	Non-loopback HTTP	Required when `--host` is not loopback; use a separate token, never the Hevy API key.
`XDG_CACHE_HOME`	`~/.cache`	Local stdio	Changes the root for the npm update-check cache at `hevy-mcp/update-check.json`.
`SENTRY_DSN`	Packaged project DSN	Optional local Node telemetry	Overrides the Sentry destination. An empty value disables Sentry export. The Worker does not import Node telemetry.
`SENTRY_RELEASE`	`hevy-mcp@<installed-version>`	Optional local Node telemetry	Overrides the release label attached to local Sentry events and traces.
`-h`, `--help`	N/A	Local stdio CLI	Print supported options and exit.
`-v`, `--version`	N/A	Local stdio CLI	Print the installed version and exit.

The local Node executable uses stdio by default. Opt into local Streamable HTTP with:

HEVY_API_KEY=your-hevy-api-key npx hevy-mcp --transport http --host 127.0.0.1 --port 3000

The local MCP endpoint is http://127.0.0.1:3000/mcp; non-loopback binds require the separate HEVY_MCP_HTTP_BEARER_TOKEN environment variable. A Docker deployment must publish the port explicitly:

docker run --rm -p 3000:3000 -e HEVY_API_KEY -e HEVY_MCP_HTTP_BEARER_TOKEN \\
  ghcr.io/chrisdoc/hevy-mcp:latest --transport http --host 0.0.0.0 --port 3000

This Node HTTP mode is distinct from the stateless Cloudflare Worker HTTP endpoint described above: the Node server owns stateful client sessions, while the Worker is designed for hosted deployment and does not import Node code.

Cache behavior

search-exercise-templates and hevy://exercise-templates share a server-scoped in-memory catalog cache:

Entries live for five minutes, and the cache holds at most one catalog.
Concurrent catalog requests share an in-flight fetch when possible.
search-exercise-templates accepts refresh: true to invalidate the cache.
Paginated get-exercise-templates calls always fetch their requested page.
Each hosted Worker request gets a fresh cache, preventing cross-key sharing.

Security and mutations

Keep HEVY_API_KEY out of source control, URLs, logs, and screenshots.
Local clients provide the key through the child process environment.
Hosted clients send the key only in the Authorization: Bearer header. The Worker validates each key with Hevy, does not store it, and sends it upstream only as Hevy's api-key header.
Browser requests must come from an exact allowlisted origin. The default allowlist includes Claude.ai, ChatGPT, VS Code for the Web, and github.dev; self-hosted deployments can override it with MCP_ALLOWED_ORIGINS.
Local development can copy .dev.vars.example to .dev.vars to disable Origin validation for MCP Inspector. PR preview Workers use the same development-only setting because their browser origins are dynamic. Never set MCP_DISABLE_ORIGIN_CHECK=true on a production Worker.
Create operations can produce duplicates when retried. Update operations replace existing records. Review tool inputs and use client confirmations.

Troubleshooting

The server does not appear: restart or reconnect your MCP client after changing its configuration.
npx fails: confirm that Node.js 20 or newer is installed, then run npx -y hevy-mcp --version in a terminal.
Codex cannot see the server: run codex mcp list, then start a new Codex session after confirming the hevy entry exists.
Hosted authentication fails: confirm the key is active, belongs to a Hevy PRO account, and is sent as Authorization: Bearer <HEVY_API_KEY>.
Local authentication fails: confirm the key is active and available to the MCP child process as HEVY_API_KEY.
Need diagnostics: set HEVY_MCP_DEBUG=1. Diagnostic output goes to stderr and does not interfere with MCP messages on stdout.

If you find a bug or have a feature request, open an issue.

Contributing

Contributions are welcome. Developer setup, testing lanes, generated-client workflows, Cloudflare Worker deployment, and pull request rules are documented in CONTRIBUTING.md.

License and acknowledgements

License: MIT
Credits: Model Context Protocol and Hevy Fitness

Hevy MCP

At a glance

README

Hevy MCP Server

Read-only CLI

See it in action

What can you do with it?

Quick start

1. Get your Hevy API key

2. Connect `hevy-mcp` to your client

Connect to the hosted endpoint

Codex

Other Streamable HTTP clients

Run locally instead

Codex

Claude Desktop or Cursor

Google Antigravity

Option A: Automatic Plugin Installation (Recommended)

Option B: Manual Configuration (No Plugin)

Any stdio MCP client

3. Ask your first question

How it works

Guided prompts

Tools

Resources

Hosted Cloudflare endpoint

OAuth for Claude.ai and other remote MCP clients

Self-host the Worker

Advanced configuration

Cache behavior

Security and mutations

Troubleshooting

Contributing

License and acknowledgements

Comments (0)

Hevy MCP

At a glance

README

Hevy MCP Server

Read-only CLI

See it in action

What can you do with it?

Quick start

1. Get your Hevy API key

2. Connect hevy-mcp to your client

Connect to the hosted endpoint

Codex

Other Streamable HTTP clients

Run locally instead

Codex

Claude Desktop or Cursor

Google Antigravity

Option A: Automatic Plugin Installation (Recommended)

Option B: Manual Configuration (No Plugin)

Any stdio MCP client

3. Ask your first question

How it works

Guided prompts

Tools

Resources

Hosted Cloudflare endpoint

OAuth for Claude.ai and other remote MCP clients

Self-host the Worker

Advanced configuration

Cache behavior

Security and mutations

Troubleshooting

Contributing

License and acknowledgements

Comments (0)

2. Connect `hevy-mcp` to your client