Deposit detail
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| limit | No | Max intents to return (default: 100). | |
| cursor | No | Pass the previous page's `next_cursor` to walk forward without offset drift. This is the supported pagination path on every list endpoint. | |
| offset | No | Deprecated. Use `cursor` instead — offset pagination is fragile under concurrent writes and slow at scale. Still accepted for backwards compatibility while integrators migrate. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It offers no behavioral information such as whether the tool is read-only, has side effects, requires authentication, or has rate limits. The single word 'detail' is insufficient.
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 extremely terse (two words) but suffers from under-specification. It is not structured to be helpful for an AI agent; it lacks any context, examples, or clarity.
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 is severely incomplete given the tool's complexity (4 parameters, no output schema, no annotations). It does not explain return values, pagination behavior (cursor/offset), or how to interpret results. An agent would struggle to use this tool correctly.
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 schema covers 75% of parameters with descriptions, but the tool description adds no additional meaning. For instance, the required 'id' parameter lacks description, and the description does not clarify its purpose or format. The description adds no value beyond the schema.
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 'Deposit detail' is vague and essentially restates the tool name. It fails to specify what action is performed (e.g., retrieve, fetch) or what exactly is returned. It does not distinguish from sibling tools like get_deposit_context.
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 is provided on when to use this tool versus alternatives. There is no mention of required prerequisites, common use cases, or when to prefer this over other get_* tools.
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.
