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Nexus Memory

Nexus Memory

by Neboy72
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

remember

Store facts, rules, preferences, and procedures for AI agents so they persist across sessions and remain available for later recall.

Instructions

Store a memory for AI agents. Persists information across sessions.

Input Schema

NameRequiredDescriptionDefault
textYesThe memory content to store
scopeNoOptional project/agent area label ([a-z0-9-], max 40 chars). Scoped memories are excluded from OTHER agents' auto-prefetch (only the agent whose NEXUS_SCOPE matches sees them automatically); explicit recall() always finds them. Omit or 'default' = visible to every agent's auto-prefetch.default
sourceNoWhere this memory came from (e.g. 'conversation', 'document', 'cron')
categoryYesMemory category (state-prefixing scope): fact, belief, session, rule, preference, temp. Required for state-prefixing — the server applies 'fact' as a backward-compatible default when the client omits this field.fact
confidenceNoOptional: Confidence score (0.0-1.0) attached to the provenance. Use 0.9+ for verified facts, 0.5-0.8 for beliefs/inferences, <0.5 for speculative notes. The server applies a sensible default (0.7) when omitted.
source_urlNoRecommended: URL or origin reference for provenance tracking. When set, the server activates Justification-Check (Rung 2) on recall: the URL is checked via async HTTP HEAD and the result is returned as `verification` (`verified`, `unreachable`). Optional — omit to skip verification (the memory will be returned with `verification: "unchecked"` on recall).
access_levelNoWho can see this: public (all agents), trusted (approved agents), private (only owner)private
effective_fromNoOptional ISO-8601 date/datetime: when this fact became valid (temporal validity). Defaults to now. Use for retro-dated imports (e.g. mail import with the original mail date).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.22.25
    • changedInput schema / properties / access_level / default
      Previous value: -"public"New value: +"private"
  2. Changed1 schema field changedv0.18.7
    • addedInput schema / properties / scope
      Added value: +{
+  "default": "default",
+  "description": "Optional project/agent area label ([a-z0-9-], max 40 chars). Scoped memories are excluded from OTHER agents' auto-prefetch (only the agent whose NEXUS_SCOPE matches sees them automatically); explicit recall() always finds them. Omit or 'default' = visible to every agent's auto-prefetch.",
+  "type": "string"
+}
  3. Changed1 schema field changedv0.16.0
    • addedInput schema / properties / effective_from
      Added value: +{
+  "default": null,
+  "description": "Optional ISO-8601 date/datetime: when this fact became valid (temporal validity). Defaults to now. Use for retro-dated imports (e.g. mail import with the original mail date).",
+  "type": "string"
+}
  4. First observedv0.13.1

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, yet it only discloses cross-session persistence. It is silent on duplicate handling, whether re-storing an existing fact creates a new entry or whether update should be used instead, and on any write-related constraints.

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?

Two lean sentences with zero filler, front-loading the core action. It is efficient, though arguably too sparse given the tool's complexity rather than padded.

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

Completeness2/5

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

For an 8-parameter mutation tool with no annotations and no output schema, the description is thin: it omits the recall/update/forget relationship, duplicate-handling semantics, and any note on how scoped or verified memories behave on write. The rich schema compensates for parameter detail but not for the missing behavioral framing.

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?

Schema description coverage is 100%, so the schema already documents all 8 parameters in detail (scope isolation, confidence heuristics, source_url verification, access levels, temporal validity). The description adds no parameter meaning beyond that, so the baseline of 3 applies.

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

Purpose4/5

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

States a specific verb ('Store') and resource ('a memory') and adds the distinguishing trait that it persists across sessions. However, it never names the retrieval counterpart (recall) or the mutation siblings (update, forget), so differentiation is left to inference from the sibling list.

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

Usage Guidelines2/5

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

No guidance on when to use this versus recall, update, or forget. The 'persists across sessions' line hints at intent but does not state triggering conditions, prerequisites, or exclusions.

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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