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AiAgentKarl

Agent Memory MCP Server

memory_store

Save key-value data persistently across sessions with optional tags and namespaces. Ideal for storing facts, preferences, and context.

Instructions

Wissen persistent speichern.

Speichert einen Key-Value-Eintrag der über Sessions hinweg erhalten bleibt. Ideal für Fakten, Präferenzen, Kontext.

Args: key: Eindeutiger Schlüssel (z.B. "user_preference_language") value: Der zu speichernde Inhalt (Text, JSON, etc.) namespace: Namespace zur Trennung (z.B. "project_x", "user_123") tags: Optionale Tags zum Kategorisieren (z.B. ["preference", "important"])

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
valueYes
namespaceNodefault
tagsNo
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It mentions persistence across sessions but omits details such as idempotency, duplicate key handling, side effects, or any security/rate limit considerations. This is insufficient for a write operation.

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 concise, with a clear title line, a short explanation, and a structured Args list. Every sentence adds value and there is no redundancy.

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

Completeness3/5

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

For a simple store tool with 4 parameters and no output schema, the description covers purpose, parameters, and usage context. However, it lacks details on return values, error handling, and duplicate key behavior, which limits completeness.

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 schema coverage is 0%, so the description must add meaning. The Args section explains each parameter: key as unique identifier, value as the content, namespace for separation, tags for categorization. This provides semantic context beyond the schema's type/default information.

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 'Wissen persistent speichern' (persistently store knowledge) and explains it stores a key-value entry that persists across sessions. The verb 'speichern' (store) and resource 'Key-Value-Eintrag' are specific, and the tool is distinct from siblings like memory_retrieve and memory_delete.

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

Usage Guidelines3/5

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

The description says 'Ideal für Fakten, Präferenzen, Kontext' (ideal for facts, preferences, context), giving usage context but no explicit guidance on when not to use or alternatives. It implies usage for persistent storage but does not differentiate from siblings.

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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