Mnemoverse Memory

memory_stats

Read-onlyIdempotent

Get an overview of the stored memory: total count, episodes vs consolidated prototypes, number of learned associations, the list of domains, and average quality scores. This memory is shared across all AI tools the user has connected to Mnemoverse. Use it to orient yourself, to confirm the exact domain name before writing to it, or when the user asks what you remember. Read-only — changes nothing.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`domains`	Yes	User-defined memory domains.
`episodes`	No	Number of episodic (not yet consolidated) memories.
`prototypes`	No	Number of consolidated prototype memories.
`avg_valence`	No	Average valence of stored memories: how well recalls turned out, on a scale from -1 to 1.
`memory_count`	Yes	Number of saved memories.
`hebbian_edges`	No	Number of Hebbian concept-to-concept links, learned from concepts that occur together as memories are stored and used.
`avg_importance`	No	Average importance of stored memories, on a scale from 0 to 1.

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedSep 25, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedOutput schema / properties / avg_importance

Added value: +{
+  "description": "Average importance of stored memories, on a scale from 0 to 1.",
+  "type": "number"
+}

addedOutput schema / properties / avg_valence

Added value: +{
+  "description": "Average valence of stored memories: how well recalls turned out, on a scale from -1 to 1.",
+  "type": "number"
+}

addedOutput schema / properties / episodes

Added value: +{
+  "description": "Number of episodic (not yet consolidated) memories.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}

addedOutput schema / properties / hebbian_edges

Added value: +{
+  "description": "Number of Hebbian concept-to-concept links, learned from concepts that occur together as memories are stored and used.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}

addedOutput schema / properties / prototypes

Added value: +{
+  "description": "Number of consolidated prototype memories.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}

First observedSep 22, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description's 'Read-only — changes nothing' restates the schema. However, it adds valuable non-obvious context: the memory is shared across all AI tools connected to Mnemoverse. It also describes what the overview includes, providing behavior beyond what annotations specify.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with no filler. It front-loads the operation and its main outputs, then adds the shared-memory context and usage guidance, ending with a clear read-only note. Every sentence contributes distinct information.

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?

For a zero-parameter read-only tool with an output schema available, the description covers the operation, the returned data categories, the shared-memory scope, and practical use cases. Nothing needed for correct invocation is missing.

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?

The tool has zero parameters and an empty input schema, so no parameter documentation is needed. The baseline of 4 applies because the description cannot add parameter meaning to a tool that takes no inputs.

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 clearly states the verb ('Get an overview') and the resource ('stored memory'), then enumerates the specific outputs: total count, episode vs. prototype breakdown, learned associations, domains, and average quality scores. This is specific enough to be distinguished from all sibling tools such as memory_read or memory_write, even without naming them.

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

Usage Guidelines4/5

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

The description provides explicit usage contexts: 'to orient yourself, to confirm the exact domain name before writing to it, or when the user asks what you remember.' This gives clear routing guidance, though it does not explicitly state when not to use the tool or name alternative tools beyond the implied writing context.

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

All Mnemoverse Memory tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.