Langfuse MCP vs Health Export MCP

A side-by-side look at the Langfuse MCP 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.

Langfuse MCP logoLangfuse MCPMonitoring · Local subprocess (stdio)Query Langfuse traces, debug exceptions, analyze sessions, and manage prompts. Full observability toolkit for LLM applications.65GreatAuth: api key requiredHealth Export MCP logoHealth Export MCPMonitoring · Local subprocess (stdio)Query 190 Apple Health metrics from any MCP agent — zero-dependency, read-only, local-first.67GreatAuth: no auth required

Verdict: choose Langfuse MCP 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?

Langfuse MCP logoChoose Langfuse MCP when

  • You need dedicated capabilities in the Monitoring domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: API key required.
  • You have the keys it needs: LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, LANGFUSE_HOST, LANGFUSE_MCP_READ_ONLY.
  • You want tools like list_annotation_queues, create_annotation_queue, get_annotation_queue.
Explore Langfuse MCP

Health Export MCP logoChoose 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.
Explore Health Export MCP

Feature & specification comparison

Rows where the two servers differ are marked.

SpecLangfuse MCP logoLangfuse MCPHealth Export MCP logoHealth Export MCP
CategoryMonitoringMonitoring
Quality signal65/100 · Great67/100 · Great
Install commandConfirmedConfirmed
TransportLocal subprocess (stdio)Local subprocess (stdio)
AuthAPI key requiredNo auth required
PricingFreeFree
Required env varsLANGFUSE_PUBLIC_KEYLANGFUSE_SECRET_KEYLANGFUSE_HOSTLANGFUSE_MCP_READ_ONLYHEALTH_DATA_DIR
Verified ownerCommunity listingCommunity listing
GitHub stars1138
Directory activity 6 views 0 installs 0 upvotes 9 views 0 installs 0 upvotes
Tools4814

Tools & capabilities

Langfuse MCP tools 48

  • list_annotation_queuesList annotation queues with pagination.
  • create_annotation_queueCreate an annotation queue.
  • get_annotation_queueGet a single annotation queue by ID.
  • list_annotation_queue_itemsList items in an annotation queue.
  • get_annotation_queue_itemGet a specific annotation queue item by queue and item ID.
  • create_annotation_queue_itemCreate an annotation queue item.
  • update_annotation_queue_itemUpdate the status of an annotation queue item.
  • delete_annotation_queue_itemDelete an annotation queue item.
  • create_annotation_queue_assignmentAssign a user to an annotation queue.
  • delete_annotation_queue_assignmentUnassign a user from an annotation queue.
  • list_datasetsList all datasets in the project with pagination. Returns metadata about datasets including name, description, item count, and timestamps. Args: ctx: Context object containing lifespan context with Langfuse client page: Page number for pagination (starts at 1) limit: Maximum items per page (max 100) Returns: A dictionary containing: - data: List of dataset metadata objects - metadata: Pagination info (page, limit, total)
  • get_datasetGet a specific dataset by name. Retrieves dataset details including metadata and item count. Args: ctx: Context object containing lifespan context with Langfuse client name: The name of the dataset to fetch Returns: A dictionary containing dataset details: - id: Unique dataset identifier - name: Dataset name - description: Dataset description - metadata: Custom metadata - items: List of dataset items (if included by the API) - runs: List of dataset runs (if included by the API)
  • +36 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.

Langfuse MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "avivsinai-langfuse-mcp": {
      "command": "uvx",
      "args": [
        "langfuse-mcp"
      ],
      "env": {
        "LANGFUSE_PUBLIC_KEY": "YOUR_LANGFUSE_PUBLIC_KEY_HERE",
        "LANGFUSE_SECRET_KEY": "YOUR_LANGFUSE_SECRET_KEY_HERE",
        "LANGFUSE_HOST": "YOUR_LANGFUSE_HOST_HERE",
        "LANGFUSE_MCP_READ_ONLY": "YOUR_LANGFUSE_MCP_READ_ONLY_HERE"
      }
    }
  }
}

Health Export MCP

mcpServers (Claude Desktop / Cursor)
{
  "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

Langfuse MCP is categorized under Monitoring and uses a local stdio subprocess. Health Export MCP belongs to Monitoring and uses a local stdio subprocess. Pick Langfuse MCP 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.

Langfuse MCP is listed as free. Auth: api key required. 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 avivsinai-langfuse-mcp 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, Langfuse MCP has a quality signal of 65/100 (Great) with 6 views, 0 installs and 113 GitHub stars. Health Export MCP has 67/100 (Great) with 9 views, 0 installs and 8 GitHub stars.