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bcornish1797

MCP-Memory-LanceDB-Pro

by bcornish1797

memory_recall

Search long-term memories using hybrid retrieval (vector similarity + full-text) with cross-encoder reranking to return semantically relevant results ranked by quality.

Instructions

Search long-term memories using hybrid retrieval (vector similarity + BM25 full-text + cross-encoder reranking). Returns semantically relevant memories ranked by quality.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat you want to remember — natural language
limitNoMax results (default: 5)
scopeNoFilter: agent:primary, agent:secondary, global, project:alpha, project:beta
categoryNo
Behavior4/5

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

With no annotations, the description discloses the hybrid retrieval approach and quality ranking, indicating a read-only operation. It does not cover performance or error conditions, but the main 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.

Conciseness5/5

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

Two short sentences: the first defines the verb and resource, the second explains the return value. Every word earns its place, with no redundancy.

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?

The description covers the core function and output quality, and the schema handles parameters. It could briefly mention output format or examples, but for a search tool with 4 well-described parameters, it is sufficiently complete.

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?

The schema already documents all parameters with descriptions (75% coverage). The tool description adds no per-parameter details beyond the schema's own descriptions, so it meets the baseline but does not add extra semantics.

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 clearly states it searches long-term memories using a specific hybrid retrieval method, distinguishing it from sibling tools like memory_list (simple listing) and memory_extract (extraction).

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 implies usage for semantic search but provides no explicit guidance on when to use this tool over alternatives like memory_list or memory_extract.

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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