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arman-tech

spatial-memory-mcp

by arman-tech

import_memories

Import memories from CSV, JSON, or Parquet files with validation, deduplication, and dry-run mode. Run dry_run first to verify records before committing.

Instructions

Import memories from file with validation. Use dry_run=true first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoImport format (auto-detected from extension)
dry_runNoValidate without importing
validateNoValidate records before import
_agent_idNoOptional agent identifier for request tracing and per-agent rate limiting.
deduplicateNoSkip records similar to existing memories
source_pathYesPath to source file
dedup_thresholdNoSimilarity threshold for deduplication
namespace_overrideNoOverride namespace for all imported memories
regenerate_embeddingsNoGenerate new embeddings (required if vectors missing)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.11.4

TDQS

B3.3/5.0
Behavior3/5

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

No annotations exist, so the description carries the disclosure burden. It does add a meaningful safety behavior (dry-run first) and mentions validation, but it does not disclose the mutation/persistence side effects of a real import, how deduplication/embedding regeneration behave, or any rate/limits. This is minimal but not absent.

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 two short sentences with the primary action front-loaded and the safety instruction second. It is efficient, though a little more context about what dry-run produces or what happens on a real import would make it more useful.

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?

Despite the rich schema, this is a 9-parameter mutating operation with no annotations and no output schema. The description does not state what the tool returns, what a successful import changes, what a dry run reports, or how it relates to remember_batch/export_memories. The two-sentence summary leaves material gaps for an agent deciding whether and how to call it.

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?

The input schema already has 100% description coverage for all 9 parameters, so the baseline is 3. The description adds only the directive to set dry_run=true first; it does not explain formats, paths, or the dedup/embedding parameters, so it provides no additional semantic lift.

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 clearly states the action ('Import memories'), the object ('memories'), and the source ('from file'), and adds a validation qualifier. It does not explicitly contrast itself with sibling tools such as remember_batch or export_memories, but 'from file' is enough to signal bulk file import.

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?

'Use dry_run=true first' provides a concrete, safe invocation sequence, which is useful guidance. However, the description never states when to choose this tool over alternatives or when not to use it, so the selection context remains implicit.

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