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mcp-hyperspace-memory

mcp-hyperspace-memory

Official
by YARlabs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

memory_query_planner

Breaks raw user queries or compliance conditions into parallel sub-queries and proof obligations, using chat context and available collections to guide HyperspaceDB memory retrieval.

Instructions

Alias for hyperspace_query_planner.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "raw_user_query": "<raw_user_query>"
    },
    "name": "memory_query_planner"
  }
}

Input Schema

NameRequiredDescriptionDefault
contextNoOptional previous conversation context or chat history to resolve coreferences.
collectionsNoOptional list of available HyperspaceDB collections.
raw_user_queryYesThe raw user query or compliance condition submitted to the agent.
max_sub_queriesNoMaximum number of parallel proof obligations to generate.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.2.0

TDQS

D1.9/5.0
Behavior1/5

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

No annotations are provided, so the description carries the entire burden of behavioral disclosure. Calling it an alias says nothing about what the tool does, what it returns, whether it mutates anything, or what the generated 'proof obligations' mentioned in the schema actually are.

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 single sentence is free of padding and front-loaded, but its brevity comes from under-specification rather than economy. There is no wasted wording, yet almost nothing of substance is conveyed.

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?

A four-parameter planning tool with no annotations and no output schema needs the description to explain its behavior, and this one supplies none of it. The agent cannot determine what a 'sub query' or 'proof obligation' is or what the planner produces without consulting another tool's definition.

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?

Schema description coverage is 100%, with all four parameters documented in the schema itself, so the baseline of 3 applies even though the description adds no parameter meaning. The alias sentence does nothing to clarify raw_user_query, collections, context, or max_sub_queries.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description consists solely of 'Alias for hyperspace_query_planner,' which identifies the tool only by reference to a sibling and never states what operation it performs. It does not name a verb, resource, or domain, leaving the agent to open the sibling tool to learn anything at all.

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?

'Alias' weakly implies the two tools are interchangeable, which hints at usage but supplies no guidance on when to pick this one over hyperspace_query_planner or whether either is preferred. No prerequisites, exclusions, or context are given.

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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