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Zehee

Kimi Code Memory MCP Server

by Zehee

search_context

Search conversation rounds across all workspace sessions by keyword and optional date range to retrieve relevant past context.

Instructions

Search conversation rounds across all workspace session wires by keywords and optional date range. Default detail: 'normal' keeps output within ~6000 chars. Use detail: 'compact' for a quick overview (no match text, no cluster members). Use detail: 'full' when you need full match text and all cluster members.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of matching rounds to return
queryYesKeywords to search for in conversation rounds
detailNoOutput detail level. 'normal' (default) returns truncated text and cluster members within the output budget. 'compact' returns only references/counts. 'full' disables the budget and returns longer text.
date_toNoOptional end date in YYYY-MM-DD format
date_fromNoOptional start date in YYYY-MM-DD format
max_cluster_sizeNo单个 cluster 最多包含的 turn 数,防止连续讨论过长时上下文爆炸。默认 15。
max_output_charsNoMaximum output length in characters for normal mode. Default 6000. Ignored in compact/full.
cluster_gap_secondsNo相邻 turn 被归为同一「簇」的最大时间间隔(秒)。一个簇代表一段连续的讨论或决策。默认 90 秒;协作节奏慢可适当调大,话题切换快则调小。

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.4.2

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the disclosure burden. It usefully reveals output-budget behavior and how detail levels change the returned content. It does not mention side effects, but 'search' implies a read operation, and the key truncation behavior is clearly disclosed.

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 three sentences with the primary action front-loaded, followed by concise detail-mode guidance. Every sentence adds useful information and there is no filler.

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

Completeness4/5

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

For a search tool with full schema parameter coverage, the description supplies the missing behavioral context: output size, detail-level trade-offs, and cluster-member visibility. It does not describe the result shape for empty results or explicitly address sibling alternatives, but overall it is sufficient for an agent to select and invoke the tool correctly.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds practical meaning beyond the schema by explaining the trade-offs among compact, normal, and full detail, and by tying normal mode to the 6000-char output budget. This helps an agent choose the right parameter value.

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 states the verb and resource: search conversation rounds across all workspace session wires by keywords and optional date range. It is specific enough to convey the tool's scope, though it does not explicitly differentiate itself from sibling tools like 'search' or 'recall'.

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 gives practical guidance on when to use each detail level: compact for a quick overview, normal as the default with a ~6000-char output budget, and full when complete match text and cluster members are needed. However, it does not explicitly state when to use this tool instead of alternative 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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