Skip to main content
Glama

kb_search

Search a persistent knowledge base using lexical or semantic search with hybrid fusion. Retrieve relevant entries by query and optional filters.

Instructions

Search knowledge base. Lexical FTS5 (or LIKE fallback) by default; set semantic=true / hybrid=true / search_mode=hybrid to use vector embeddings + RRF fusion (requires LORE_SEMANTIC_SEARCH=true).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
topicNo
top_kNo
semanticNo
hybridNo
search_modeNo
session_idNo
parent_query_idNo
required_requeryNo
caller_agentNo
min_trust_scoreNo
min_scoreNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must convey behavior. It describes the default lexical search and the optional vector modes with RRF fusion, but fails to mention what happens if the required env var is missing, or any error handling. It does not discuss rate limits, authentication, or side effects, though search is read-only.

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 a single sentence that efficiently conveys the core functionality and key options. It is concise but could benefit from brevity in technical details; overall, it is well-structured and front-loaded.

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

Completeness2/5

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

Given the tool's complexity (12 parameters, multiple search modes, an output schema exists), the description is incomplete. It does not explain many parameters, output format, error conditions, or how the default fallback works. The reliance on technical terms (FTS5, RRF fusion) may also assume too much prior knowledge.

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?

Schema description coverage is 0%, so the description must explain parameters. It only covers 4 of 12 parameters (query, semantic, hybrid, search_mode), leaving important params like top_k, session_id, min_score, etc. unexplained. This insufficiently compensates for the lack of schema descriptions.

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 states 'Search knowledge base' and details the search modes (FTS5, semantic, hybrid), clearly identifying the tool's function. The name 'kb_search' combined with the description distinguishes it from sibling tools like 'search_local' or 'search_corpora', though it could be more explicit about when to use this over other search tools.

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 explains how to enable semantic/hybrid search (setting flags and requiring an environment variable). However, it does not specify when NOT to use this tool or direct users to alternatives like 'multi_search' for broader searches, lacking comprehensive usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/davidgut1982/lore-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server