Datasieve vs Health Export MCP
A side-by-side look at the Datasieve and Health Export MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Datasieve for monitoring work as a local process; choose Health Export MCP for monitoring as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Datasieve when
- You need dedicated capabilities in the Monitoring domain.
- You prefer a local stdio subprocess transport.
- You want tools like
create_watch, watch_status, drain_events.
Choose Health Export MCP when
- You need dedicated capabilities in the Monitoring domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You have the keys it needs:
HEALTH_DATA_DIR. - You want tools like
get_mcp_status, list_metrics, get_health_metrics.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Monitoring | Monitoring |
| Quality signal | 57/100 · Good | 67/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | None listed | HEALTH_DATA_DIR |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 8 |
| Directory activity | 1 views 0 installs 0 upvotes | 9 views 0 installs 0 upvotes |
| Tools | 19 | 14 |
| Full listing | View Datasieve | View Health Export MCP |
Tools & capabilities
Datasieve tools 19
create_watchBuy a standing watch from DataSieve (https://api.datasieve.xyz). standard = $0.10/7d, 1 condition, 50 triggers; composite = $0.25/7d, up to 5 any-match conditions (e.g. 5 heartbeat dead-man switches), 200 triggers; standard30 = $0.35/30d and composite30 = $0.85/30d — one payment covers the month, for agents that will not be awake to renew weekly. Payment is a gasless USDC transfer signed locally. Events go to your webhookUrl (HMAC-signed) if set, and always to a server-side mailbox drained with drain_events; every event carries a signed Ed25519 observation receipt you can replay to third parties. Failed calls are never billed. The watch id + secret are remembered locally so later calls need only the id.watch_statusState, heartbeat lastCheckedAt, triggersUsed/cap, expiry, delivery stats, and for dead-man switches: up/down, lastPingAt, nextDeadline, pingUrl. Secret is looked up from local state if omitted.drain_eventsCollect everything the watch caught — works with zero infrastructure (the mailbox pattern). Pass `since` = last seen event id for incremental drains.renew_watchExtends the watch one more period (7 days, or 30 on the *30 tiers) at its tier price and resets the trigger budget. Renewing a paused watch also reactivates it.delete_watchpause_watchStop a watch firing (chain, web, heartbeat, schedule) without deleting it. The expiry clock keeps running. Use before a planned agent shutdown so your dead-man switch does not cry wolf.resume_watchBacklog-free resume: heartbeat deadlines restart from now and schedules jump to their next FUTURE slot — nothing that elapsed during the pause replays.cron_nextNext N run times for a cron expression in any IANA timezone, plus seconds-until-next. If the goal is for something to HAPPEN at those times, create_watch with a schedule condition instead — DataSieve fires the cron as signed webhooks for the life of the watch.x402_pingThe cheapest possible real x402 purchase: proves this wallet + client can pay a production seller before you point it at anything expensive. Returns payer + network; failed calls are never billed.verify_receiptEvery DataSieve event carries receipt {alg, keyId, statement, sig} — an Ed25519 attestation that DataSieve observed the event. This checks it against the service key, so an agent can validate evidence handed to it by ANOTHER agent without trusting that agent.ping_heartbeatKeep a dead-man switch alive. Pass the pingUrl from create_watch (or a watchId whose ping URLs are in local state). Call this at least once per intervalSeconds.service_healthScanner cursor lag vs chain head — verify the watcher is alive before you buy.- +7 more on the listing page
Health Export MCP tools 14
get_mcp_statusHealth check: data source, how many metrics/workouts are available, which optional context files exist, and the most recent data date. Call this first to confirm the bridge is connected.list_metricsList every available Apple Health metric with its unit, day count, and date range. Use this to discover metric names before querying.get_health_metricsGet values for a metric (or all metrics) over an optional date range, with an aggregate (avg/sum/min/max/latest). The core data-retrieval tool. Every result carries a `coverage` block giving the metric's real firstDate/lastDate/days: check it before trusting a long window, and note that `aggregate` is always computed over the full range even when `points` are rolled up. Single-metric answers also list any logged point events inside the window as segmentBoundaries.get_trendsCompare the most recent N-day window against the prior N days for a metric: change, percent change and direction (up/down/flat). Also returns `daysAvailable` and `windowSatisfied`: if windowSatisfied is false the file does not hold enough history for the window you asked for, and the comparison is over less data than requested. Logged point events inside the compared span are listed as segmentBoundaries.compare_periodsCompare a metric between two arbitrary date periods (A vs B): each aggregate plus the change and percent change. Pass periodA/periodB explicitly, or pass anchor {eventId, days} to build both periods around a logged event (the before/after question, with the event day excluded from both sides).get_structured_exportReturn clean structured JSON for the chosen metrics/date range. Paginated: the result carries `nextCursor` when more metrics remain; pass it back as `cursor` for the next page. Prefer naming the metrics you need and a date range; calling it bare over a full history is a lot of data.get_intradayThe current hour-by-hour window from the iOS app's HOURLY automations (health-intraday.json, app 1.4+): each metric's hourly points plus its latest value. The file is REPLACED on every hourly run, so this is a live within-day view, not history; use get_health_metrics for day-level questions. Returns available:false with setup guidance when no hourly automation has delivered yet.query_health_dataNatural-language convenience: pass a question and get routed structured results. Prefer the specific tools above when you can, and call list_metrics first to see how much history exists, since this tool answers over whatever the file holds.list_eventsLogged context events from health-events.json: medication starts, habit changes, doctor visits, life events, shift blocks, episodes, travel, and any type a newer app adds. Optional {type, tag, start, end} filters; a range event matches a window it overlaps. Sorted ascending by date. Returns available:false when the file was never exported; absence means nothing was exported, not that nothing happened.get_profileThe context fields the user explicitly opted in to sharing (health-profile.json): conditions, medications, goals, allergies, notes. Returns the fields plus a presentFields list. An absent field was withheld by the user or never enabled; absence must never be read as "none".get_workoutsQuery the workouts cache with {activityType (a name like Running, or a raw HealthKit id like 37), start, end} filters and pagination ({limit} default 50 max 200, {cursor} from a previous nextCursor). Records are returned exactly as stored, including the newer optional keys (avgHeartRate, maxHeartRate, running dynamics, cycling power, intervals, hasRoute) when the app exported them; older caches simply lack those keys and nothing is fabricated. Also returns summary {count, byActivityType} over everything that matched.get_sleep_sessionsClustered sleep sessions from health-sessions.json with {start, end, day} filters. Sessions are attributed to the WAKING day, matching the daily cache's sleep_analysis, so the two surfaces never disagree; a split night appears as multiple sessions with the same day, returned as-is. Timestamps carry the local UTC offset at the time of the sample.- +2 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Datasieve
{
"mcpServers": {
"datasieve": {
"command": "npx",
"args": [
"-y",
"datasieve-mcp"
]
}
}
}
Health Export MCP
{
"mcpServers": {
"io-github-philipad-health-export-mcp": {
"command": "npx",
"args": [
"-y",
"health-export-mcp"
],
"env": {
"HEALTH_DATA_DIR": "YOUR_HEALTH_DATA_DIR_HERE"
}
}
}
}
Frequently asked questions
Datasieve is categorized under Monitoring and uses a local stdio subprocess. Health Export MCP belongs to Monitoring and uses a local stdio subprocess. Pick Datasieve for monitoring work and Health Export MCP for monitoring.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Datasieve has no declared pricing — check the project's own site. Health Export MCP is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add datasieve and io-github-philipad-health-export-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Datasieve has a quality signal of 57/100 (Good) with 1 views, 0 installs and 0 GitHub stars. Health Export MCP has 67/100 (Great) with 9 views, 0 installs and 8 GitHub stars.