实时行情快照（实时与快讯） 每只证券的最新盘中快照，交易时段持续刷新；非交易时段返回上一交易日收盘快照。 需要 PRO 及以上套餐（低档位调用返回 403）。
Args: symbol: 证券代码，逗号分隔可批量（至多 200 个）；不传返回全市场
Returns: JSON 数组；字段: symbol, name, price, open, high, low, pre_close, volume, amount, trade_time, pct_chg
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | No | 证券代码，逗号分隔可批量（至多 200 个）；不传返回全市场 |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
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 a heavy burden, and it does well by disclosing the subscription requirement (PRO+, 403 otherwise) and the temporal snapshot behavior. It does not mention pagination or rate limits, but for a simple snapshot tool the disclosed context is substantive.
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 well-structured with a title line, a behavior paragraph, and Args/Returns sections. It is efficient and front-loaded with the core purpose. Minor redundancy: the first line '实时行情快照' is restated, and the parenthetical '（实时与快讯）' adds little value, but overall it is not bloated.
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?
Given the tool's simplicity (one optional parameter) and the presence of an output schema, the description covers the essential context: what it returns, when it updates, and the subscription gate. It does not describe ordering or pagination, but these are not critical for this snapshot tool. The description is sufficiently complete for an agent to select and invoke it 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?
Schema description coverage is 100%, and the description's Args section repeats the schema's parameter description verbatim without adding new meaning. The optional comma-separated batch of up to 200 symbols is already in the schema, so the description adds no parameter semantics beyond the structured definition.
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 the tool provides real-time market snapshots ('实时行情快照') for each security, with explicit behavior during trading and non-trading hours. This distinguishes it from siblings like 'daily' (historical daily bars) and 'express' (news flash) by focusing on the latest intraday tick-level snapshot.
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?
The description gives clear temporal context: during trading hours it refreshes continuously, and outside trading hours it returns the previous close. It also notes the PRO subscription requirement and 403 error for lower tiers. However, it does not explicitly name alternative tools or state when NOT to use this tool, so it falls short of a 5.
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.
Several tools have overlapping purposes or unclear names, such as daily vs etf_daily vs index_daily vs fx_daily, and fundamentals vs technical_factors_pro (which also includes PE/PB). top_inst and top_list are also easily confused. Descriptions help, but the names alone are not always sufficient to distinguish them.
All names use lowercase with underscores, which is consistent, but there is variation in number (daily vs stocks), specificity (daily vs index_daily), and verbosity (top_inst vs top_list). The pattern is not uniform across the set, making it less predictable.
45 tools is on the heavy side for an MCP server, and there is redundancy (technical_factors and technical_factors_pro overlap significantly). For a broad financial data API, the count is justifiable, but it borders on overwhelming.
The tool set covers a wide range of financial data: quotes, fundamentals, technicals, financial statements, corporate actions, money flows, ETF data, index data, and news. There are minor gaps (e.g., no bond data) but the core domain of Chinese A-share/ETF/FX data is well covered.