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Glama

Connecticut DMV

by io.github.pipeworx-io

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)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare idempotentHint=true and non-destructive, but description adds key behavioral details: scoped by identifier, persistence differences for authenticated vs anonymous users, and 24-hour retention for anonymous sessions. No contradiction.

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?

Four well-structured sentences conveying purpose, usage, storage behavior, and pairing with sibling tools. No redundant or extraneous content.

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?

Covers purpose, usage, and behavior sufficiently. No output schema, but the tool is straightforward; description does not need to detail return values. Lacks mention of edge cases like overwriting existing keys, but overall complete.

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% with clear descriptions for both parameters. The description adds example values but no additional semantic meaning beyond what the schema provides.

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 clearly states what the tool does ('Save data the agent will need to reuse later'), uses specific verbs and resources, and distinguishes from sibling tools like recall and forget by mentioning them.

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

Usage Guidelines5/5

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

Explicitly states when to use the tool ('when you discover something worth carrying forward') and provides alternatives by pairing with recall and forget. Also contrasts with anonymous and authenticated users.

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

All Connecticut DMV toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Several tools are near-identical in purpose: ask_pipeworx and ask_pipeworx_beta are explicitly the same right now, while ai_visibility_check and scan_competitor_ai_presence overlap heavily. The only DMV-specific tool is otherwise buried among generic research, prediction-market, memory, and subscription tools that an agent would struggle to separate.

Naming Consistency3/5

Most tools use snake_case, but conventions are mixed: some are verb_noun (list_subscriptions, generate_llms_txt), some are bare verbs (remember, forget), some are brand-prefixed nouns (pipeworx_trending, polymarket_edges), and ask_pipeworx lacks a conventional verb pattern. Still readable, but not a cohesive naming scheme.

Tool Count1/5

32 tools is already heavy, but nearly all of them are unrelated to the stated Connecticut DMV scope. The server would be better served by a handful of DMV-focused tools; the current count is an extreme mismatch between name and content.

Completeness1/5

The only DMV tool is ct_dmv_ev_registrations, covering EV registration counts from a single February 2025 snapshot. There is no general vehicle registration lookup, driver licensing, plate/ VIN search, appointment, or form coverage, so the DMV domain is severely incomplete.

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