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Remember

remember
Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

TDQS

A4.4/5.0
Behavior5/5

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

Adds context beyond annotations: scoping by identifier, persistence duration for authenticated vs anonymous users. No contradictions with 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?

Description is compact and front-loaded with purpose. No redundant sentences, but could be slightly more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple memory tool, description covers purpose, usage, behavioral aspects, and references sibling tools. No output schema needed.

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 coverage is 100%, so baseline is 3. Description adds examples for key naming conventions and value type, but does not significantly enhance meaning beyond schema.

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 verb 'save' and resource 'data the agent will need to reuse later', with specific examples like 'resolved ticker, target address'. Differentiates from siblings by referencing recall and forget.

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?

Explicitly says when to use: 'Use when you discover something worth carrying forward'. Provides context on scoping and persistence. Could further mention when not to use, but complementary tools are implied.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools occupy the same general query/research space: ask_pipeworx, ask_pipeworx_beta (currently identical), ask_pipeworx_grounded, deep_research, validate_claim, entity_profile, and recent_changes all overlap in what they can return. The descriptions are detailed and try to steer usage, but the boundaries are fuzzy enough that agents can easily select the wrong tool.

Naming Consistency3/5

All names are snake_case and descriptive, but there is no consistent verb_noun convention across the set. It mixes bare verbs (remember, recall, forget), noun phrases (entity_profile, recent_changes), domain-prefixed families (securitytrails_*, polymarket_*), and Pipeworx meta-tools (ask_pipeworx_*), so the pattern is predictable only within each family.

Tool Count2/5

35 tools is above the 25+ threshold for a coherent MCP surface, and many are highly specialized (Polymarket arbitrage, AI visibility checks, npm dependency scans) rather than core Securitytrails functionality. The set feels like multiple products merged into one rather than a well-scoped toolset.

Completeness3/5

The broad data-research workflows are well covered: routing, entity resolution, profiling, comparison, validation, subscriptions, memory, and basic Securitytrails domain lookups. But for a server named Securitytrails, there are obvious missing security-intelligence operations such as associated domains, IP/certificate enrichment, and broader DNS infrastructure enumeration.