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dakera-mcp

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by Dakera-AI
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Rust
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dakera_search

Search an AI agent's persistent memory semantically, filtering results by tags or memory type when constraints matter.

Instructions

Semantic search with optional tag and memory-type pre-filters. Prefer over dakera_recall when results must be constrained by tag or type alongside the semantic match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoen, de, fr, es, it, pt or nl (v0.12+)
tagsNoFilter by tags
queryYesSearch query text
top_kNoNumber of results
agent_idYes
memory_typeNoFilter by memory type

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.11.0
    • addedInput schema / properties / lang
      Added value: +{
+  "description": "en, de, fr, es, it, pt or nl (v0.12+)",
+  "type": "string"
+}
  2. Addedv0.10.12
  3. Removedv0.10.11
  4. Addedv0.10.8

TDQS

A3.7/5.0
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. It implies a read-only search and notes the filters are 'optional', but says nothing about ordering/ranking, default top_k behavior, result limits, or permissions — significant gaps for an unannotated retrieval tool.

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?

Two tight sentences with zero waste; the capability statement is front-loaded and the routing rule follows immediately.

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?

Purpose and sibling routing are complete and params are well covered by the schema, but with no output schema and no annotations the description leaves return format, ranking, and default result count unaddressed for a 6-parameter retrieval tool.

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 83%, so the schema already documents nearly all parameters. The description only restates the tag and memory_type filters, adding no syntax, format, or defaulting detail beyond what the schema provides.

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?

States a specific verb+resource ('Semantic search') and adds the differentiator that it supports optional tag and memory-type pre-filters. It explicitly names a sibling (dakera_recall), so an agent can separate the two without opening schemas.

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?

Gives a clear routing rule: 'Prefer over dakera_recall when results must be constrained by tag or type alongside the semantic match.' It does not address the other search siblings (dakera_fulltext_search, dakera_hybrid_search), so the guidance is directional rather than exhaustive.

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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