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mcp-hyperspace-memory

mcp-hyperspace-memory

Official
by YARlabs
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TypeScript
Hybrid

memory_recall

Retrieve ranked, semantically relevant memories for a query, with optional filters for session, memory type, or minimum importance to support agent recall.

Instructions

Retrieve the most relevant memories for a query from collection 'agent_cognitive_memories_129' using semantic similarity. Filter by session_id, memory_type ('semantic'|'episodic'|'procedural'), or min_importance (1-10). Returns a JSON object with query, filters, and ranked memories with cognitive scores.

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": {
      "query": "<query>"
    },
    "name": "memory_recall"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of memories to retrieve (default: 5).
queryYesWhat to search for in memory.
session_idNoOptional: filter results to a specific session identifier.
memory_typeNoOptional: filter by memory type.
min_importanceNoOptional: filter memories with importance >= min_importance (1-10).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.2.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full disclosure burden. It does well to state the ranking method and the returned JSON shape (query, filters, ranked memories with cognitive scores), but it omits whether the operation is read-only (implied but unstated), how ranking ties or empty results behave, and whether there is a result cap beyond 'limit'.

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?

Three sentences, front-loaded with the core action, then filters, then return shape — a sensible order with little waste. The filter enumeration slightly duplicates the schema, which keeps it just short of a 5.

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?

With no output schema, the description correctly compensates by sketching the return object, and it covers all five parameters at least by name. What remains thin — pagination, ordering guarantees, empty-result behavior — is minor for a single-shot retrieval tool.

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%, so every parameter is already documented in the schema; the description only restates the filter names and the 1-10 importance range. It adds no semantics beyond the structured fields, which is the expected baseline when the schema does the heavy lifting.

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?

States a specific verb and resource ('Retrieve the most relevant memories for a query') plus the mechanism ('semantic similarity') and the source collection, which distinguishes it from memory_remember/memory_forget. It stops short of naming which sibling to use instead for hierarchical traversal or planning, so it is clear but not fully differentiated.

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 retrieval use case is implied by 'most relevant memories for a query,' and the filters hint at narrowing scenarios, but there is no explicit when-to-use guidance versus memory_explore_hierarchy, memory_query_planner, or memory_list_sessions. An agent must infer the routing decision itself.

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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