Vaultbeat MCP Server

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State of mind (moods)

get_state_of_mind

Read-onlyIdempotent

Retrieve and decrypt recent State of Mind records locally, including Apple Health and AI-logged moods with valence, labels, and associations. Filter by date range or partner.

Instructions

Decrypt recent states of mind (how the person felt) locally — both sources.

SENSITIVE. Apple Health's "State of Mind": each record is one feeling with valence (-1 very unpleasant … 0 neutral … +1 very pleasant), valence_classification (Apple's seven regions, veryUnpleasant … veryPleasant — use these words rather than inventing a grade), labels (Apple's feeling words: drained, stressed, calm, grateful…), associations (the life area: work, family, partner, health…), kind (momentaryEmotion = how they felt at that moment, dailyMood = how the day went overall), local_date / local_time. source says where it came from: · "apple_health" — logged by the person on their Watch, in the Health app or in another app, and imported by their iPhone (app names it); · "ai" — recorded by an AI through log_state_of_mind (entry_id, note). Remove a mistaken one with delete_state_of_mind. Each owner also carries daily (per day: count, mean_valence, lowest_valence, highest_valence, daily_mood_valence) and counts per region, label and life area. Describe what was logged; a day with one record says far less than a day with ten — quote count beside any average, and never read a day with no record as a neutral day.

By default the newest 100 records (about three months of daily moods). since / until ("YYYY-MM-DD", local days, both inclusive) read a calendar window instead — "how was I in March", or anything older than the default page — and then limit applies only if you pass it. A record with its tallies is roughly 450 bytes, so about 130 fit in one result; a longer window comes back as result_too_large — read it a month or a quarter at a time.

Returns YOUR records by default; partner=true returns your partner's — only if they turned on sharing their moods with your AI in their own Vaultbeat app (off by default). Stays on-device, never re-exported.

Carries a coverage block: quote coverage.days_covered (distinct days, not the row count) and coverage.span_days beside any average or trend. coverage.window_satisfied: false alone does NOT mean a short history: it is also false when older days exist beyond your window. 🔴 Before saying how far back someone's data goes, read coverage.more_available: true means this server can decrypt records OLDER than first_day that your read left behind — read them with a since / until window ending before first_day (a much larger limit does not fit in one result), or quote coverage.oldest_available as the real start of their history. Never report a limit-shaped window as the extent of their data.

Input Schema

Name	Required	Description	Default
`fresh`	No
`limit`	No
`since`	No
`until`	No
`partner`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.9.3Oct 19, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already establish the safe-read profile (readOnly, idempotent, non-destructive, closed world), and the description goes well beyond them: it flags the data as SENSITIVE, states it stays on-device and is never re-exported, discloses the `result_too_large` failure mode with its size math, and explains the `coverage` block, `window_satisfied`, and `more_available` semantics so the agent does not misreport history extent. This is unusually rich behavioral context.

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?

Purpose is front-loaded and the dense body is mostly load-bearing (window semantics, coverage interpretation, size limits). It is long and occasionally repetitive — the coverage/more_available guidance restates itself across several sentences — but almost every line changes how the agent should call or interpret the tool.

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

Completeness5/5

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

An output schema exists, so return shape needn't be spelled out, yet the description still supplies the interpretive context an agent needs (per-record fields, per-owner daily tallies, the warning not to treat a record-less day as neutral, and how to quote `count` and `coverage` beside averages). For a multi-source, paged, sensitive read tool this is complete.

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?

Schema description coverage is 0%, so the description carries the full burden, and it does so for four of five params: `since`/`until` format and inclusivity, `limit`'s conditional application, and `partner`'s sharing precondition. The `fresh` parameter is never mentioned in either the schema or the description, leaving one gap.

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

Purpose5/5

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

States a specific verb and resource ('Decrypt recent states of mind') with an immediate gloss of what the resource means ('how the person felt'), and distinguishes itself from the write path by naming `log_state_of_mind` and `delete_state_of_mind` as the tools for recording/removing. An agent can separate this read tool from its siblings without opening a schema.

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

Usage Guidelines5/5

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

Explicitly covers when to use the default page (newest 100), when to switch to a `since`/`until` window ('how was I in March', data older than the default page), how `limit` interacts with a window, how to page around the ~130-record result cap, and the condition for `partner=true`. It also routes removal to `delete_state_of_mind`. Nothing is left to inference.

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