Recent transactions of any Solana wallet, parsed human-readable: type, protocol, description, fee, failures (Helius enhanced). Costs $0.02 USDC per call (x402, Solana mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | tx count, 1-25, default 10 | |
| wallet | Yes | Solana wallet address (base58) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and does well: it discloses cost ($0.02 USDC), network (Solana mainnet), data source (Helius enhanced), and output parsing fields. It doesn't cover rate limits or error behavior, but for a read-only wallet fetch this is strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler; the core purpose is front-loaded and the second sentence adds only the essential cost/network caveat. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description compensates by listing the main returned fields and warning about cost. It is mostly complete for a simple wallet activity query, though pagination/ordering details and invalid-wallet behavior are not specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents wallet and limit. The description adds the notion of recency and human-readable parsing but no parameter-specific detail beyond the schema, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a clear verb+resource: fetching recent transactions for any Solana wallet, and enumerates parsed fields (type, protocol, description, fee, failures). The activity focus distinguishes it from siblings like get_wallet_holdings, though it doesn't name alternatives explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: an agent should call this when it needs recent wallet transaction history. However, there is no explicit when/when-not guidance or mention of alternatives such as get_wallet_holdings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools are tightly scoped and cross-referenced, but the set contains overlapping families: liquidation tools (alert/scan/history/stats/leaders/recent/heatmap) and redundant snapshots like get_market_snapshot vs get_trade_context, get_last_liquidation vs get_recent_liquidations, and get_cascade_forecast_free vs get_cascade_forecast. Agents will need to read descriptions carefully to avoid misselection.
All tool names follow a consistent get_<domain>_<detail> snake_case pattern, which makes the API predictable. The only real deviations are the bare 'pricing' tool and the 'free' suffix on taster variants.
At 52 tools, this far exceeds the 3-15 well-scoped range and crosses the 50-tool extreme threshold. The count is inflated by numerous paid/free taster pairs and many overlapping liquidation variants.
The surface covers prices, funding, open interest, orderbooks, liquidations, wallet/token data, Solana network health, DeFi TVL, and stablecoin flows—broad coverage for a crypto data feed. Gaps like historical OHLC/price candles, a machine-readable symbol list, and pagination endpoints are workable around but would round it out.