mnemo-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mnemo-mcpremember that the user prefers JSON format"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mnemo-mcp
Portable cognitive memory for AI agents. An MCP server with semantic search and decay.
What it does
Gives any MCP-compatible AI agent persistent memory that behaves like human memory:
Memories decay unless reinforced — noise fades, important things stick
Deduplication — same content bumps weight instead of duplicating
Namespaced — multiple agents can share or isolate their memories
Semantic search — find memories by meaning, not keywords
Pluggable embeddings — Ollama (local) or any OpenAI-compatible API
Multi-agent — author tracking so you know who remembered what
Related MCP server: AI Long-Term Memory MCP Server
Quick start
npx mnemo-mcpNode version note: mnemo uses native addons (
better-sqlite3,sqlite-vec) that are compiled for a specific Node ABI version. If you switch Node versions (e.g. via nvm), the cached npx install may break. Fix:rm -rf ~/.npm/_npx/ && npx -y mnemo-mcp, or use one of the stable install methods below.
Stable install (recommended for MCP clients)
For MCP clients like Claude Code or Claude Desktop, a global install avoids npx cache issues:
npm install -g mnemo-mcpThen configure your client with "command": "mnemo-mcp" instead of npx.
Alternatively, run from source:
git clone https://github.com/skye-flyhigh/mnemo-mcp.git
cd mnemo-mcp && npm install && npm run buildThen point your client to "command": "node", "args": ["/path/to/mnemo-mcp/dist/cli.js"].
CLI commands
Consult help
npx mnemo-mcp helpHelp section:
Usage:
mnemo-mcp Start MCP server (default)
mnemo-mcp export [--md] [--ns <ns>] Export memories as JSON or markdown
mnemo-mcp search <query> [-n <limit>] Semantic search from terminal
mnemo-mcp inspect [<id>] [--ns <ns>] View a memory or aggregate stats
mnemo-mcp decay Run a decay cycle
mnemo-mcp count [--ns <ns>] Quick count
mnemo-mcp help Show this help
Options:
--ns <namespace> Filter by namespace
--md Export as markdown (default: JSON)
-n <number> Limit search results (default: 10)
Environment:
MNEMO_DB_PATH Database path (default: ~/.mnemo/memory.db)
MNEMO_EMBEDDING_PROVIDER ollama | openai (default: ollama)
MNEMO_EMBEDDING_MODEL Model name
MNEMO_EMBEDDING_BASE_URL Provider URL
MNEMO_EMBEDDING_API_KEY API key (openai only)
MNEMO_DIMENSIONS Vector dimensionsEmbedding provider
Ollama (default, local) — no API key needed, fully offline:
ollama pull nomic-embed-textOpenAI-compatible (cloud) — set provider + API key in your MCP client config:
MNEMO_EMBEDDING_PROVIDER=openai
MNEMO_EMBEDDING_API_KEY=sk-...This covers OpenAI, Azure OpenAI, Together AI, Voyage AI, Jina, and any service that speaks the /v1/embeddings format.
Configuration
All config is passed via env vars through your MCP client config. Defaults work out of the box with Ollama.
Variable | Default (ollama) | Default (openai) | Description |
|
| — |
|
|
|
| Model name |
|
|
| API base URL |
| — | (required) | API key for cloud providers |
|
|
| Embedding vector dimensions |
|
|
| SQLite database path |
Supported Clients
Works with any app that supports the Model Context Protocol:
Client | Platform | Notes |
Claude Desktop | Mac, Windows | Local + remote MCP servers |
Claude Code | Terminal | Full MCP support |
Claude.ai | Web | Remote MCP servers |
ChatGPT | Web | Developer Mode (Pro/Plus/Business/Enterprise) |
Cursor | Mac, Windows, Linux | AI code editor |
Windsurf | Mac, Windows, Linux | AI code editor |
VS Code | Mac, Windows, Linux | Via Continue, Cline, or Copilot-MCP extensions |
Codex (OpenAI) | Terminal | CLI coding agent |
Amazon Q | Terminal, IDEs | AWS coding assistant |
Zed | Mac, Linux | Code editor with MCP support |
BoltAI | Mac, iOS | Multi-provider AI chat |
Chatbox | Mac, Windows, Linux, Web | Open-source AI chat (37K+ stars) |
And 500+ more MCP clients. If your app supports MCP, mnemo works with it.
Client Setup Examples
Claude Code
Add to .claude.json (globally under "/Users/you" or per-project):
{
"mcpServers": {
"mnemo": {
"type": "stdio",
"command": "npx",
"args": ["mnemo-mcp"],
"env": {}
}
}
}Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"mnemo": {
"command": "npx",
"args": ["mnemo-mcp"]
}
}
}With OpenAI embeddings
Pass provider config through the env block:
{
"mcpServers": {
"mnemo": {
"command": "npx",
"args": ["mnemo-mcp"],
"env": {
"MNEMO_EMBEDDING_PROVIDER": "openai",
"MNEMO_EMBEDDING_API_KEY": "sk-..."
}
}
}
}Tools
Tool | Description |
| Store a memory with tag, categories, and namespace |
| Store multiple memories in a single call (batch embedding) |
| Semantic search by query (default 10 results, no hard cap) |
| Delete a memory by ID |
| Patch an existing memory's content or metadata (re-embeds if content changes) |
| Reinforce a memory's weight (+0.1 default) |
| Run a decay cycle (tag-based weight reduction) |
| View a specific memory or aggregate stats |
Decay System
Memories have a tag that controls how fast they fade:
Tag | Rate | Use case |
| 0.0 | Never decays — identity, values |
| 0.01/cycle | Slow decay — relationships, key facts |
| 0.05/cycle | Normal decay — conversations, observations |
Weight floor is 0.1 — memories never fully disappear.
Deduplication
Mnemo prevents memory drift with three layers of dedup:
Timing-based — identical content within 10 seconds is silently dropped
Hash-based — exact duplicate content bumps the existing memory's weight instead of duplicating
Semantic — if new content is very similar to an existing memory (vector distance < 0.12), the existing memory's weight is bumped instead
Roadmap
Pluggable embedding backends (Ollama local, OpenAI-compatible API)
Published to npm (
npx mnemo-mcp)Register on MCP directories (Smithery, mcp.run)
CLI companion for manual memory inspection/export
Memory export/import (JSON)
License
MIT
Available Tools
8 toolsbumpC
Reinforce a memory's weight (recall reinforcement)
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The memory ID to reinforce | |
| amount | No | Weight increase amount (default 0.1) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, placing full burden on the description. It only states the action (reinforce) without disclosing side effects, reversibility, or what 'weight' means in the memory system. Lacks critical 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (a phrase), which is concise but borderline too terse. It lacks a full sentence structure and could be more informative without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no output schema), the description does not fully explain the effect on the memory system, prerequisites, or expected outcomes. It is adequate only for the most basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema provides 100% coverage with descriptions for both parameters (id and amount). The description adds no additional semantic value beyond what the schema already conveys, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action: reinforce a memory's weight for recall reinforcement. It provides a specific verb and resource, distinguishing it from sibling tools like decay (opposite) and update. However, it could more explicitly differentiate from similar operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as decay, update, or recall. No prerequisites or conditions are provided, leaving the agent to infer context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
decayB
Trigger a decay cycle — reduces memory weights based on tag tiers
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It states the core action but omits details on side effects, destructiveness, permissions required, or idempotency. The brief mention of 'tag tiers' gives some context but is insufficient for a safe understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence of 12 words, efficiently conveying the tool's purpose without any fluff. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters, no output schema, and no annotations, the description is minimally adequate. However, it lacks explanation of what 'decay cycle' entails, the meaning of 'memory weights' and 'tag tiers', and any preconditions or consequences, which would be necessary for full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema coverage is 100% (vacuously). Per guidelines, 0 parameters yields a baseline of 4. The description adds no additional meaning beyond the empty schema, but no clarification is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Trigger' and resource 'decay cycle', specifying the action 'reduces memory weights based on tag tiers'. It is distinct from sibling tools like 'forget' or 'update', but lacks explicit differentiation, preventing a top score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'forget', 'bump', or 'update'. The description does not include when-not-to-use or context for optimal application, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetADestructive
Delete a memory by ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The memory ID to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already include destructiveHint: true, indicating destruction. Description adds 'Delete' which aligns. However, no additional behavioral details (e.g., irreversibility, side effects) beyond 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no extraneous words. Efficiently conveys the essential operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-param destructive tool with annotation, the description is minimal but sufficient. However, more context (e.g., permanence, recovery options) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'id' described. Description echoes the schema's description ('The memory ID to delete'), adding no new meaning. Baseline score of 3 for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Delete' and resource 'a memory', with 'by ID' clarifying the identifier. Clearly distinguishes from sibling tools like 'recall' (retrieve) and 'remember' (create).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., when not to delete, or prerequisites like existence of memory). Description only states the action without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
inspectARead-only
View a specific memory or aggregate stats
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Memory ID to inspect (omit for stats) | |
| namespace | No | Filter stats by namespace |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true. Description adds dual-mode behavior (specific memory vs. stats) beyond annotations, enhancing transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no extraneous information, perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two fully described parameters, no output schema, and sibling list, the description covers all necessary usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. Description does not add significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states two distinct functions: viewing a specific memory by ID or aggregate stats. Differentiates from siblings like 'recall' which likely retrieves multiple memories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage via input fields (id for specific, omit for stats) but does not explicitly state when to use inspect versus other retrieval tools like recall or search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recallC
Search memories semantically by query
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 10, no hard cap) | |
| query | Yes | The search query | |
| project | No | Filter by project | |
| minWeight | No | Minimum weight threshold | |
| namespace | No | Filter by namespace | |
| categories | No | Filter by categories |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist to pre-declare safety or behavior. The description only states 'semantically', implying some form of search but lacks details on performance, ordering, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief (4 words). While concise, it is not structured as a full sentence and omits important context. It is not verbose, but could benefit from a slightly richer structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters, no output schema, and no annotations, the description lacks critical information about return format, pagination, or result semantics, making it incomplete for an agent to confidently use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all 6 parameters with descriptions (100% coverage). The tool description adds no additional meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action (search), resource (memories), and method (semantically by query). It distinguishes from siblings like 'remember' and 'forget', but does not explicitly differentiate from 'inspect', which might also involve retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are no examples, prerequisites, or context indications.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rememberB
Store a memory with optional tag, categories, and namespace
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Decay tier: core=permanent, crucial=slow decay, default=normal decay | |
| author | No | Who created this memory | |
| source | No | Origin context (tool, conversation, consolidation) | |
| content | Yes | The text content to remember | |
| project | No | Project scope for filtered retrieval | |
| namespace | No | Scope isolation (e.g., 'echo', 'cat', 'shared') | |
| categories | No | Semantic categories (e.g., ['preference', 'user']) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but only states 'store a memory'. It does not mention side effects, defaults for optional parameters, or what happens on duplicate content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with purpose, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite 7 parameters, the description is very brief. It does not explain return values, default behavior for required content, or how the memory is stored (e.g., success/failure).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented already. The description adds minimal value beyond listing optional parameters, which is already clear from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Store' and resource 'memory', and mentions optional parameters, distinguishing it from sibling tools like recall (retrieve) or forget (delete).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like remember_batch or bump. The description does not provide context for selection or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remember_batchA
Store multiple memories in a single call. Embeds all at once for efficiency. Deduplicates automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| memories | Yes | Array of memories to store |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses embedding and deduplication, but omits details on atomicity, error handling, or side effects, which are important for a batch mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, each adding value without redundancy. Front-loaded with key action and benefits.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite reasonable behavioral hints, the description lacks crucial completeness for a batch tool: no mention of return values, partial success handling, or success/failure indicators. Output schema is absent, increasing the burden.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds 'array of memories' context but doesn't provide new semantics beyond what the schema offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description explicitly states the tool stores multiple memories in a single call, highlighting efficiency and deduplication. This clearly differentiates it from sibling tools like 'remember' (single memory) and 'forget' (removal).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for batch storage, contrasting with single-call alternatives. However, it doesn't explicitly state when not to use it or compare to 'remember', leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
updateB
Update an existing memory's content or metadata. Re-embeds automatically if content changes.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The memory ID to update | |
| tag | No | New decay tier | |
| source | No | New source context | |
| content | No | New content (triggers re-embedding) | |
| project | No | New project scope | |
| namespace | No | New namespace | |
| categories | No | New categories (replaces existing) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses automatic re-embedding on content change, which is a key behavioral trait. However, with no annotations, the description carries full burden; it does not cover error handling, side effects, or reversibility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with purpose and key behavioral note. No wasted words; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters and no output schema or annotations, the description is too brief. Missing details on return behavior, error states, and side effects beyond re-embedding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover all 7 parameters (100% coverage), so the description adds no new information. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Update an existing memory's content or metadata' with specific verb and resource. However, it does not distinguish from sibling tools like bump or decay, which have overlapping update semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like bump or decay. The description implies use for content/metadata changes but lacks context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
8 tool updates
v1.2.1- First observed
bump - First observed
decay - First observed
forget - First observed
inspect - First observed
recall - First observed
remember - First observed
remember_batch - First observed
update
TDQS
Scored across 8 tools
Each tool targets a distinct memory operation: storage (remember, remember_batch), retrieval (recall, inspect), modification (update, bump, decay), and deletion (forget). No overlapping purposes.
Most tools use single verbs (bump, decay, forget, inspect, recall, remember, update) which is consistent, but remember_batch breaks the pattern with a compound name. Minor deviation.
Eight tools cover all core memory lifecycle operations (CRUD plus weight management and batch storage) without being excessive. Well-scoped for a memory management system.
Covers create, read, update, delete, weight manipulation, and batch operations. Minor gap: no explicit listing of all memories without a semantic query, but semantic recall may suffice for typical use.
Maintenance
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