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remember

Store one or more new memories (concepts, decisions, findings). Before filing, search for related content first — use the search results to infer the domain: if related memories exist in a domain, file there. Prefer existing domains over creating new ones; only propose a new domain if no related content is found anywhere. Single: pass fields directly — returns {memory, suggested_connections}. Batch: pass {items:[{label,domain,...},...]} — returns {memories:[{memory,suggested_connections},...]}. After filing, review suggested_connections for agreement or contradiction with what you just filed — not only for connect opportunities. Semantic similarity reflects aboutness, not agreement; the server surfaces candidates that may warrant your review but never asserts they conflict. When a filed memory is close enough to an existing memory that they may be worth comparing, the response also includes possible_contradicts=true and possible_contradicts_candidates (id, node_kind, semantic_distance, authority_severity) — same aboutness-not-agreement caveat: the server flags these as worth your attention, never as confirmed contradictions. Review them and call connect(relationship=contradicts) if you judge they actually conflict. ALWAYS call connect for any suggested_connections you accept before ending your session (batch: connect each accepted candidate). On failure, content[0].text is JSON: {"error_class": "conflict|retryable|forbidden|validation|internal", "message": "..."}. Switch on error_class: retry on retryable, surface message on validation, treat conflict as duplicate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoOptional caller-supplied id instead of an auto-generated one. For idempotent external imports: if a memory with this id already exists, remember fails with error_class=conflict rather than overwriting it — call recall(id) to check first, or treat a conflict response as already-imported.
tagsNo
itemsNo
labelNo
domainNo
node_kindNoClassification of this memory. One of: 'transient' (temporary, will expire), 'decision' (a specific decision made, default), 'standing' (a durable rule or principle), 'reference' (a person, system, or org — referential rather than propositional knowledge), 'issue' (an open question or problem), 'option' (a considered alternative), 'assumption' (an unverified premise), 'finding' (an observed fact or result), or 'goal' (a desired outcome). Absent defaults to 'decision'. Takes precedence over the transient bool field when both are supplied.
transientNo
related_toNo
descriptionNo
occurred_atNoWhen this event actually happened (not when it is being filed). Format: YYYY-MM-DD or RFC3339. Two cases: (a) Events you directly witnessed during the current session (e.g. a decision made in the live conversation) — set occurred_at without asking; if the user did not specify a date, use today. (b) Inferred or back-dated historical events you did not directly observe — propose+confirm: state the date and your reasoning, ask the user to confirm, and only set occurred_at once confirmed. Never guess a historical date and never infer it silently from context. Turn-boundary rule: when proposing to file something as significant, the proposal must be the only action in that turn — do not include occurred_at in any remember or revise call in the same message as the proposal. Only set occurred_at in a subsequent call, after the user has replied. Always set why_matters when using occurred_at.
why_mattersNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The description discloses many non-obvious behaviors beyond the sparse annotations: suggested_connections reflect aboutness not agreement, possible_contradicts are flagged as candidates rather than confirmed conflicts, and failures return a structured error_class with explicit handling rules ('retry on retryable, surface message on validation, treat conflict as duplicate'). These details substantially exceed what annotations provide.

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?

The description is long but logically ordered: purpose, pre-filing search, invocation shapes, post-filing review, contradiction handling, connect mandate, and error handling. Each sentence adds a distinct piece of guidance with minimal redundancy, though the continuous prose format could be more scannable with paragraph breaks or bullet lists.

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

Completeness4/5

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

For a complex write tool without an output schema, the description thoroughly covers return values ({memory, suggested_connections}, {memories:[...]}), the error JSON structure, domain inference, and the mandatory connect step. It does not explicitly explain every parameter, but many are self-explanatory or covered by the schema, making the description complete enough for correct invocation in most cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema coverage at only 27%, the description compensates partially by clarifying the two invocation shapes ('Single: pass fields directly' and 'Batch: pass {items:[{label,domain,...},...]}') and their return formats. However, several parameters (tags, transient, why_matters, related_to) are not explained beyond the sparse schema, leaving their meanings to inference. The compensation is partial, not complete.

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?

The description opens with 'Store one or more new memories (concepts, decisions, findings)', naming a specific verb (store), resource (memories), and scope (new). It clearly differentiates from siblings such as recall (read), revise (update), forget (delete), and search (query) by focusing on creation, and it distinguishes the singular and batch invocation forms.

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?

The description gives explicit workflow guidance: 'Before filing, search for related content first — use the search results to infer the domain' and 'Prefer existing domains over creating new ones'. It also mandates post-action behavior with 'ALWAYS call connect for any suggested_connections you accept before ending your session', naming complementary tools (search, connect) and making the conditions for use clear.

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

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TDQS

A4.2/5.0
Disambiguation4/5

Each tool targets a distinct operation—lifecycle (remember/revise/forget), graph edges (connect/disconnect/why_connected), retrieval (recall/search/recent/history/orient/significance)—and the descriptions carefully disambiguate overlaps. However, the read/analysis cluster (recent, history, orient.recent, significance) could still cause initial misselection before reading the detailed descriptions.

Naming Consistency3/5

Names are readable and consistently lowercase, but they do not follow a single convention: most are bare verbs (connect, remember, revise, search, visualise) while others are nouns (domains, history, recent, significance) and two are multiword phrases (suggest_connections, why_connected). This mix is still predictable enough to navigate, but less coherent than a uniform verb_noun surface.

Tool Count4/5

16 tools is slightly above the typical 3–15 band, but the scope of a knowledge-graph memory server justifies the breadth: CRUD, connections, domain admin, and multiple query/analysis tools are all represented. No tool feels redundant enough to cut, though the set is at the heavy end.

Completeness4/5

Core lifecycle is well covered: create/read/update/archive/purge, connection creation/removal, domain admin, and multiple query/analysis modes. The main gap is that bulk domain merge (merge_domains) is referenced in tool descriptions but not exposed as an MCP tool, so agents must direct users to an external admin interface for that operation.

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