Skip to main content
Glama
memengine

MemoryOS MCP Server

Official
by memengine

memoryos_universal_get_context

Retrieve relevant context from cross-agent universal memory. Returns concise, formatted results to help AI agents and tools use shared knowledge.

Instructions

Retrieve cross-agent universal memory context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
formatNobullets
uui_tokenNo
agent_api_keyNo
context_max_tokensNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. The verb 'Retrieve' signals a read-only operation, which is a meaningful behavioral trait. However, it does not disclose authentication requirements, aggregation behavior, or any side effects, even though the schema hints at uui_token and agent_api_key.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is a single economical sentence with no fluff, but it is arguably too sparse for a tool with six parameters. It does not include any structural cues or parameter hints, so while concise, it is not optimally sized for the tool's complexity.

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?

The tool has six parameters, no output schema, and no annotations, yet the description only provides a high-level phrase. Critical context is missing: what query means, what formats are valid, how the token parameters work, and what the return value represents. This is inadequate for reliable tool selection and invocation.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no parameter-level meaning. Six parameters exist, including query, limit, format, tokens, and context_max_tokens, but the description does not explain any of them, leaving the agent to infer semantics entirely from names and defaults.

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 uses a clear verb ('Retrieve') and resource ('cross-agent universal memory context'), which distinguishes it from siblings like memoryos_get_context. However, it does not define what 'context' includes or how this differs from other retrieval tools beyond the 'universal' qualifier.

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?

There is no guidance on when to use this tool versus memoryos_get_context or other memory retrieval siblings. No alternative tools, exclusions, or selection criteria are mentioned.

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