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AINative-Studio

ZeroDB Agent Memory MCP Server

zerodb_search_memory

Search agent memory with natural language queries, filtering by tags, user, session, or time range to retrieve relevant memories across sessions.

Instructions

Search agent memory semantically using natural language queries. Supports cross-session search and filtering by tags, user, or time range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoOptional tags to filter results
limitNoMaximum number of results to return
queryYesNatural language query to search for in memory (e.g., "user preferences about food")
scopeNoSearch scope: session (current conversation), agent (all sessions for this agent), or globalsession
user_idNoOptional user ID to search across all sessions for this user
session_idNoOptional session ID to limit search to specific conversation
min_importanceNoMinimum importance score (0.0 to 1.0) to filter results
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains that the tool searches semantically and supports cross-session/filtering, but it does not explicitly state that it is read-only or describe result behaviors like ranking or return format. Some context is added, but not comprehensive.

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 two sentences, front-loaded with the primary verb and object, and contains no redundant phrasing. It efficiently communicates the core action and notable features, with clear structure.

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?

With no output schema and no annotations, the description should explain what the search returns (e.g., list of memories, relevance scores). It provides a high-level purpose but omits result format and any side-effect information. The misleading 'time range' also undermines completeness. The tool's moderate complexity is not fully addressed.

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

Parameters2/5

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

The input schema covers all 7 parameters with descriptions (100% coverage), giving a baseline of 3. However, the description claims filtering by 'time range,' but no such parameter exists in the schema—only tags, user_id, session_id, scope, limit, and min_importance. This misleading statement reduces clarity and adds confusion, warranting a lower score.

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 states a specific verb and resource: 'Search agent memory semantically using natural language queries.' It clearly distinguishes the tool from siblings by focusing on agent memory and cross-session capabilities, making its purpose unambiguous.

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 clear context for when to use the tool (searching agent memory) and highlights key capabilities like cross-session search and filtering. However, it does not mention exclusions or alternatives, such as when to prefer zerodb_get_context or zerodb_semantic_search.

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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