Payment platform view. Deposits, unique makers, unique takers, fulfilled intents, volume, and currency breakdown for a payment platform.
| Name | Required | Description | Default |
|---|---|---|---|
| platform | Yes | ||
| window_days | No | Lookback window in days (default 90, max 365). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lists the returned data categories (deposits, makers, takers, etc.) but does not disclose behavioral traits such as read-only nature, authentication needs, rate limits, or side effects. Without annotations, the description covers basic behavior but lacks depth.
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?
The description is concise with a single sentence that front-loads the key purpose. However, the list format could be more structured (e.g., using bullet points) to improve readability without adding length.
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?
The description lacks details on output format, units, pagination, or data shape, especially since no output schema is provided. The tool has two parameters but only 'window_days' is explained in the schema; the description does not fully compensate for the missing context.
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?
The description does not add meaning to the 'platform' parameter beyond linking it to the tool, and the schema description for 'window_days' already covers its details. With 50% schema coverage, the description should compensate for the undocumented 'platform' parameter but fails to do so.
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?
The description clearly states it's a view of payment platform metrics, listing deposits, makers, takers, intents, volume, and currency breakdown. It distinguishes from siblings like get_maker or get_taker by focusing on aggregate platform data, but could be more explicit about the retrieval action.
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?
No guidance on when to use this tool versus alternatives like get_protocol_overview or get_market_summary. The description does not specify prerequisites or exclusions, leaving the agent to infer usage context from the name alone.
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.
Most get_* and list_* tools target distinct domain entities, but several high-level analytics endpoints overlap in purpose (get_analytics_summary, get_protocol_overview, get_market_summary, get_timeseries, get_leaderboard), and pairs like get_deposit/get_deposit_context and get_vault/get_vault_analytics create close boundaries. The descriptions clarify the differences, but an agent would need to read carefully to avoid misselection.
The tool set follows a strong verb_noun pattern: get_ for single-entity or detail views, list_ for collections, plus explicit action endpoints like export_trade_log, plan_routes, and search_explorer. All names are snake_case and predictable, with no mixing of conventions.
28 tools is on the heavy side for an MCP server, even for a broad analytics domain. Most tools map to real entities, but the surface is padded by overlapping summary/analytics endpoints and separate detail, context, and analytics variants for the same resources.
The server provides broad read-only coverage of the protocol domain: deposits, intents, makers, takers, vaults, delegates, verifiers, platforms, integrators, orderbook, routes, activity, and search. Minor gaps such as no list_vaults or list_integrators are workable via search/get endpoints, and mutating operations appear out of scope for an analytics-focused server.
