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Glama

Crawlbase

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 declare readOnlyHint and idempotentHint. Description adds that omitting key lists all keys and that data is scoped to identifier. No contradictions.

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?

Two sentences plus scoping note; front-loaded purpose with no wasted words.

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 single optional parameter tool with good annotations, description covers usage, scoping, and pairing with related tools adequately.

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 covers parameter with description; description explains behavior of omitting key, adding value 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?

Clearly states verb (retrieve/list) and resource (saved memory). Distinguishes from sibling tools 'remember' and 'forget' by name.

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: to look up previously stored context. Mentions scoping and pairing with other tools. No explicit when-not, but context is clear.

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

All Crawlbase toolsInspect
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TDQS

A4/5.0
Disambiguation4/5

The toolset is largely distinct: scraping, research, prediction-market, memory, and subscription tools each have clear boundaries. The ask_pipeworx family and the six Polymarket tools are closely related variants, but their descriptions provide explicit usage guidance, so an agent can select correctly with attention.

Naming Consistency3/5

Most tools use snake_case with descriptive names, but conventions are mixed: brand-prefixed noun phrases (crawlbase_scrape, polymarket_arbitrage, pipeworx_trending) sit alongside verb_noun tools (compare_entities, validate_claim) and bare verbs (remember, subscribe). The result is readable but not predictable.

Tool Count2/5

At 34 tools, the server spans several distinct domains (web scraping, structured data research, prediction markets, memory, subscriptions, feedback), making it feel like a kitchen sink rather than a focused toolset. The count is beyond the 'heavy' threshold and would benefit from splitting into separate servers.

Completeness4/5

The research surface is thorough: routing, grounded answers, deep research, entity profiles, comparisons, claim validation, and identifier resolution cover most real-world data needs. Minor gaps exist, such as no explicit tool to fetch pipeworx:// resource URIs and no crawler management for the scraping side.

Resources