Skip to main content
Glama
arman-tech

spatial-memory-mcp

by arman-tech

visualize

Project memories into 2D or 3D coordinates using UMAP to reveal similarity clusters and visualize relationships, with optional similarity edges for spatial exploration.

Instructions

Project memories to 2D/3D for visualization using UMAP. Returns coordinates and optional similarity edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput formatjson
projectNoProject scope for this operation. Omit to auto-detect from environment. Use "*" to search across all projects.
_agent_idNoOptional agent identifier for request tracing and per-agent rate limiting.
namespaceNoNamespace filter (if memory_ids not specified)
dimensionsNoProjection dimensionality
memory_idsNoSpecific memory UUIDs to visualize
include_edgesNoInclude similarity edges

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.11.4

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses the algorithm and output but omits side effects, performance implications, or whether it's a read-only operation. Minimal disclosure for a tool with no annotation coverage.

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?

Single, front-loaded sentence with no filler. Every word is meaningful and the core purpose is stated immediately.

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?

With 7 parameters, no output schema, and no annotations, the description is too terse to fully guide an agent. It doesn't explain how to select memories (memory_ids vs namespace), what the coordinate output looks like, or how formats (json, mermaid, svg) differ.

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 covers all 7 parameters, and description adds little beyond it. The mention of 'optional similarity edges' echoes the include_edges parameter but doesn't explain the relationship between memory_ids and namespace filters or output structure.

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?

Description clearly states it projects memories to 2D/3D using UMAP for visualization, and mentions the output (coordinates and optional similarity edges). This is specific and distinguishes it from retrieval tools like recall or nearby.

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 on when to use this tool versus alternatives. The description implies visualization use case but doesn't mention when to prefer it over nearby or recall, nor any exclusions or prerequisites.

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