Skip to main content
Glama

memory_recall

Retrieve a stored value from your local memory database by providing the exact key. Returns the saved content as a string or indicates if the key is not found.

Instructions

Recall the value stored at an exact key from the local memory database.

Returns the stored value as a string, or a "not found" indicator if the key doesn't exist.

USE WHEN: you stored something via memory_store and need to retrieve it by its exact key. NOT FOR: fuzzy or substring lookup — use memory_search. For semantic similarity, use memory_semantic_search.

BEHAVIOR: pure read. Sub-millisecond. Does NOT update any access timestamp — repeated recall is invisible.

PARAMETERS: key: exact key as passed to memory_store. Case-sensitive. Required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Discloses 'pure read' and 'sub-millisecond' performance, notes no timestamp update, and explains the return value behavior (string or 'not found' indicator). No annotations exist, so description fully covers behavioral traits.

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?

Structured into clear sections (main, USE WHEN, NOT FOR, BEHAVIOR, PARAMETERS) with no extraneous text. Every sentence serves a distinct purpose, front-loaded with core action.

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

Completeness5/5

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

For a simple key-based recall tool, the description covers purpose, usage, behavior, parameters, and return behavior. With no output schema details needed, it is fully self-contained given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema coverage, description includes a dedicated PARAMETERS section explaining 'key' as exact, case-sensitive, required—adding semantics beyond the schema's type/required fields.

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 'Recall the value stored at an exact key'—a specific verb+resource. It distinguishes from siblings by mentioning memory_search and memory_semantic_search for non-exact lookups.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit 'USE WHEN' (after memory_store) and 'NOT FOR' (fuzzy/substring/semantic lookup) with direct sibling names, giving clear when-to-use and when-not-to-use 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/ContextPulse/contextpulse'

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