Skip to main content
Glama

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)

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. Description adds scoping to identifier and behavior when key omitted, 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?

Four sentences, front-loaded with action, each sentence earns its place. 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 simple tool with one optional parameter and full annotations, the description is complete: purpose, usage, scoping, and pairing are all covered.

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 parameter description. Tool description adds minimal extra beyond stating 'omit the key argument' which is redundant.

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 retrieves a value by key or lists all keys, distinguishing it from siblings 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?

Provides explicit usage context: look up stored context without re-deriving, scoped to identifier, and paired with remember/forget. Lacks explicit when-not-to-use but sufficient.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

Several tools are near-duplicates: ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx, and multiple prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage) overlap in purpose. The Solana-specific tools are distinct, but the large non-Solana cluster creates real ambiguity.

Naming Consistency3/5

All tools use snake_case, but naming styles vary widely: get_/list_ verbs, ask_pipeworx family, polymarket_* cluster, and descriptive noun-style names like entity_profile, validate_claim, generate_llms_txt, scan_dependency. There is no single consistent verb_noun convention across the set.

Tool Count1/5

With 36 tools, the count is high, but the critical problem is scope mismatch: a server named Solscan has only 5 Solana-related tools, while 31 are unrelated data/research/prediction-market utilities. This makes the tool count inappropriate for the apparent purpose.

Completeness2/5

As a Solana explorer, the set covers only account details, token holdings, token metadata, transactions, and transfers; major gaps include blocks, token price/history, NFTs, programs/staking, and more comprehensive transfer history. For the broader data-research theme, coverage is broad but scattered and lacks a single coherent domain.