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openmemkit

openmemkit

by Jlnine
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

memory_search

Read-onlyIdempotent

Search stored Markdown memory chunks using keyword, vector, or hybrid retrieval, with optional domain and date filters to find relevant context.

Instructions

Search memory chunks. mode: keyword (FTS5/LIKE, default for short queries), hybrid (keyword + vector RRF fusion, default), vector (pure cosine). Filter by domain/date_range. / 检索记忆正文。mode=keyword(关键字)、hybrid(关键字+向量融合,默认)、vector(纯向量)；支持域/日期过滤。

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "memory_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeNohybrid
queryYessearch query / 检索关键词
top_kNo
domainNodomain filter e.g. web; default */ 域过滤，默认 *
max_charsNo
date_rangeNoe.g. 2026-08 or 2026-08-20 / 日期过滤
snippet_tokensNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so safety context is covered. The description adds meaningful behavioral detail beyond the schema by naming FTS5/LIKE, RRF fusion, and cosine similarity, and by stating the default modes. It does not describe how top_k, max_chars, or snippet_tokens affect result shape, but the core behavior is transparent.

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

Conciseness4/5

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

The description is compact and front-loaded: it opens with the action, then packs mode distinctions and filter support into a short sentence. The bilingual repetition is justified by audience needs and does not feel padded.

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?

The description covers the essential purpose and mode semantics, but with 7 parameters and no output schema, the missing explanations for top_k, max_chars, and snippet_tokens leave gaps. It is adequate for a basic search call but not fully complete for an agent trying to tune results or understand return behavior.

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 only 43%, so the description needed to compensate for undocumented parameters. It does add semantics for mode and domain/date_range, but top_k, max_chars, and snippet_tokens are still left to parameter names and defaults. This is partial compensation rather than complete coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as 'Search memory chunks' and communicates its core differentiating feature: three search modes. It does not explicitly contrast with sibling tools like memory_get or memory_list, so it stops short of fully distinguishing from them, but the verb+resource+mode details are specific.

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 gives useful in-tool guidance: keyword is suggested for short queries, hybrid is the default, vector is pure cosine, and domain/date_range filtering is available. However, it does not explain when to choose memory_search over memory_get, memory_list, or memory_history, so the alternatives guidance is incomplete.

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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