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axom_mcp_memory

Destructive

Store, retrieve, search, and manage persistent memories in the Axom database for AI agents, supporting long-term context and complex tool chaining.

Instructions

Store, retrieve, search, and manage persistent memories in the Axom database.

Memory Types:

  • long_term: Reusable patterns, architectural decisions, gotchas

  • short_term: Task-specific context, debug notes, current task state

  • reflex: Learned heuristics ("Always check X before Y" patterns)

  • dreams: Experimental ideas, creative explorations

Naming Convention: [type][descriptor][YYYYMMDD] Example: bugfix_auth_timeout_20260203

Content Format (recommended): TASK|APPROACH|OUTCOME|GOTCHAS|RELATED

Actions:

  • write: Store a new memory

  • read: Retrieve a specific memory by name

  • list: List memories with optional filters

  • search: Full-text search across memories

  • delete: Remove a memory by name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesMemory operation to perform
nameNoMemory identifier (required for read/write/delete)
contentNoMemory content (required for write)
memory_typeNoType of memory storage
importanceNoImportance level
tagsNoTags for categorization
queryNoSearch query (required for search)
limitNoMaximum results to return
expires_in_daysNoOverride default expiration in days (default per type: short_term=30d, long_term=365d, reflex=90d, dreams=180d)
Behavior4/5

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

The description adds valuable behavioral context beyond what annotations provide. While annotations indicate destructiveHint=true (for delete operations), the description clarifies the full range of actions including non-destructive ones (read, list, search). It also provides memory type definitions, naming conventions, content formats, and default expiration policies - all useful behavioral information not captured in annotations.

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 well-structured with clear sections (Memory Types, Naming Convention, Content Format, Actions) and front-loads the core purpose. While comprehensive, some information could be more concise - the memory type descriptions are somewhat verbose. Overall, it's efficiently organized with minimal wasted text.

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?

For a complex tool with 9 parameters, no output schema, and rich annotations, the description provides substantial context about memory types, naming conventions, content formats, and action behaviors. However, it doesn't describe return values or error conditions, which would be helpful given the absence of an output schema. The tool's complexity warrants this level of detail.

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?

With 100% schema description coverage, the input schema already documents all 9 parameters thoroughly. The description adds some semantic context about memory types and naming conventions, but doesn't provide additional parameter-specific guidance beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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?

The description explicitly states the tool's purpose with specific verbs ('Store, retrieve, search, and manage persistent memories') and resource ('in the Axom database'). It clearly distinguishes this memory management tool from its siblings (analyze, discover, exec, transform) which appear to have different functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context about when to use different actions (write, read, list, search, delete) and memory types, but doesn't explicitly state when NOT to use this tool versus its sibling tools. It offers good internal guidance but lacks cross-tool comparison.

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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