Skip to main content
Glama
liyexiaoyi

mnemosis-mcp

by liyexiaoyi

recall

Retrieve relevant memories based on a query, supporting episodic or semantic types with optional filtering and result limits.

Instructions

Recall memories matching a query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
queryYes
top_kNo
contextNo
embedderNo
Behavior2/5

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It only says memories are recalled 'matching a query' but gives no details about return format, limits, side effects, or operational characteristics. This is minimal and insufficient for a tool with no safety annotations.

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, front-loaded sentence with no unnecessary words. It is concise and easily parsed, though it sacrifices substantive content for brevity. That is acceptable for this dimension.

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

Completeness1/5

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

Given the tool has 5 parameters, no output schema, no annotations, and many siblings, the description is severely under-specified. It fails to explain parameter semantics, return value shape, filtering behavior, or differences from similar tools. This is inadequate for effective autonomous use.

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?

With 0% schema description coverage, the description must compensate by explaining parameter meanings. It only implies 'query' and provides no information about 'kind', 'top_k', 'context', or 'embedder'. The description adds minimal value beyond the raw schema.

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 a specific action ('Recall') and resource ('memories') with a query-based selection criterion. It is clear what the tool does at a basic level, but it does not distinguish itself from sibling tools like 'search' or 'search_batch', which may also retrieve memory-related data.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or exclusions, leaving the agent without context for tool selection among the many sibling memory tools.

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/liyexiaoyi/Mnemosis'

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