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Glama

Pub Dev

by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds value by explaining scoping ('scoped to your identifier') and the relationship with other tools. No contradiction 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences long, front-loaded with the primary purpose, and each sentence adds necessary context without redundancy. Highly efficient.

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?

Given that there is no output schema, the description adequately explains the return behavior (value or list). It covers usage, scoping, pairing, and provides examples. For a simple read tool with comprehensive annotations, it is fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with a single optional 'key' parameter. The description adds meaning by stating that omitting the key lists all saved keys, and provides examples of what keys are used for (target ticker, address, research notes).

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 the tool's purpose: 'Retrieve a value previously saved via remember, or list all saved keys.' It specifies the verb (retrieve/list) and resource (stored memory values), and distinguishes from sibling tools like remember 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?

The description explains when to use the tool: 'to look up context the agent stored earlier... without re-deriving it from scratch.' It also mentions scoping and pairing with remember/forget. However, it does not explicitly state when not to use this tool versus alternatives.

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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TDQS

A4/5.0
Disambiguation3/5

Several tools have clear functional boundaries, but there is meaningful overlap at the top level: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share one routing pipeline, and ask_pipeworx_beta is currently identical to ask_pipeworx. The six polymarket_* tools also form a dense family where an agent must read long descriptions to distinguish arbitrage scanning from edge detection from fill-risk evaluation.

Naming Consistency4/5

Names are uniformly lowercase snake_case and mostly follow verb_noun or domain-prefix conventions, which makes the set much more predictable than its count suggests. Minor deviations exist: ask_pipeworx variants are product-noun phrases, polymarket_edges is a noun phrase rather than a verb-led tool, and pairs like polymarket_edges vs polymarket_edge_tracker are easy to misread.

Tool Count2/5

With 31 tools, this server is above the 25+ threshold and feels overloaded for a single MCP surface. It mixes broad data research, prediction-market analysis, memory, subscriptions, feedback, and niche utilities like generate_llms_txt, so the set is more like several related servers merged together.

Completeness4/5

The core workflow is well covered: discovery, single-answer routing, grounded verification, deep research, entity resolution, comparison, change tracking, subscription lifecycle, and even memory primitives. Missing are minor lifecycle refinements such as updating an existing subscription, and the number of overlapping entry points makes it slightly harder to guarantee the agent will always choose the intended path.

Resources