Fulcra Context MCP vs Google Health Fitbit… | AllMCPs
Fulcra Context MCP vs Google Health Fitbit MCP
A side-by-side look at the Fulcra Context MCP and Google Health Fitbit MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Fulcra Context MCP for biology, medicine and bioinformatics work as a local process; choose Google Health Fitbit MCP for biology, medicine and bioinformatics as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Fulcra Context MCP when
You need dedicated capabilities in the Biology, Medicine and Bioinformatics domain.
You prefer a local stdio subprocess transport.
Its auth model fits you: OAuth 2.0.
You have the keys it needs: FULCRA_ENVIRONMENT.
You want tools like get_workouts, annotations_catalog, create_data_type.
get_workoutsGet details about the workouts that the user has done during a period of time.
Result timestamps will include time zones. Always translate timestamps to the user's local
time zone when this is known.
annotations_catalogGet the list of all annotation data types the user has defined.
This does not get the actual values the user has recorded; for that, use the `get_records` tool.
Use this tool to get the IDs and types to pass to `get_records`.
create_data_typeCreate a user-defined data type so the user can track something new.
Choose base_type by what gets recorded: "moment" (a point in time),
"duration" (a time range), "boolean" (yes/no), "numeric" (a number,
optionally with a unit), or "scale" (a 1-5 rating with labels).
The new type appears in get_data_catalog, and recorded values are readable
with get_records. Creation is reversible with archive_data_type.
archive_data_typeArchive (soft-delete) a user-defined data type.
The type and its recorded data are recoverable with restore_data_type.
Only user-defined types (created via create_data_type or the Context app)
can be archived.
restore_data_typeRestore an archived user-defined data type.
record_dataRecord a single record for a recordable data type.
Use get_data_catalog to find data types; user-defined ones use the
"<BaseType>/<uuid>" ID form (create new ones with create_data_type).
Recorded data can be read back with get_records.
get_data_catalogGet all data types available for this user, grouped by relevant MCP tool.
Includes health and sensor measurements,
location, events, and user-defined annotation types.
Call this before requesting time-series data or raw records, and only use a
data type with the tools named in its group.
get_time_seriesGet calculated per-interval time-series values for a single data type.
Only data types that `get_data_catalog` lists as usable with this tool are
supported; other types can be read with `get_records`. Result timestamps
include time zones; translate them to the user's local time zone when known.
get_recordsRetrieve the raw records of any data type during a time period.
Works with every type listed by `get_data_catalog`, including user-defined
ones ("<BaseType>/<uuid>" IDs); the correct API endpoint is chosen
automatically. Records that cover a time range are included when any part
of it intersects the requested window. Results are raw samples — they may
come from multiple sources and can overlap; for calculated per-interval
values of numeric data types, prefer `get_time_series`. Result
timestamps include time zones; translate them to the user's local time
zone when known.
get_data_updatesSummarize the data that arrived in the user's account during a period of time.
The time range filters on when records were processed/synced into Fulcra,
NOT on the records' own timestamps — e.g. last night's sleep records
typically arrive this morning. Use this to find out what new data exists
since a previous check, then query the changed types with the appropriate
tools.
get_sleepReturn the user's sleep data at a chosen level of detail.
Pick the coarsest level that answers the question — results grow with detail:
- "aggregate": stage totals per period (default 1 day), one row per period
per stage. Best for multi-day questions ("how did I sleep this month").
- "cycles": one row per sleep session.
- "stages": every stage interval (the full hypnogram); single-night detail.
Sleep spans midnight (starts day N, ends day N+1) — extend the time range
accordingly. Stage integers: 0=In Bed, 1=Asleep/Unknown, 2=Awake, 3=Light,
4=Deep, 5=REM. Result timestamps include time zones; translate them to the
user's local time zone when known.
get_location_at_timeGets the user's location at the given time.
If no sample is available for the exact time, searches for the closest one up to
window_size seconds away.
Result timestamps will include time zones. Always translate timestamps to the user's local
time zone when this is known.
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.
Fulcra Context MCP is categorized under Biology, Medicine and Bioinformatics and uses a local stdio subprocess. Google Health Fitbit MCP belongs to Biology, Medicine and Bioinformatics and uses a local stdio subprocess. Pick Fulcra Context MCP for biology, medicine and bioinformatics work and Google Health Fitbit MCP for biology, medicine and bioinformatics.
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.
Fulcra Context MCP is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: oauth 2.0. Google Health Fitbit MCP has no declared pricing — check the project's own site. 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 fulcradynamics-fulcra-context-mcp and google-health-fitbit-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Fulcra Context MCP has a quality signal of 63/100 (Good) with 5 views, 0 installs and 9 GitHub stars. Google Health Fitbit MCP has 57/100 (Good) with 0 views, 0 installs and 17 GitHub stars.