batch_query
Batch query multiple tickers at once for efficiency
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tickers | Yes | Comma-separated ticker symbols (e.g. AAPL,MSFT,GOOGL) |
Batch query multiple tickers at once for efficiency
| Name | Required | Description | Default |
|---|---|---|---|
| tickers | Yes | Comma-separated ticker symbols (e.g. AAPL,MSFT,GOOGL) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / endpointsRemoved value: -{
- "description": "Array of endpoint names (e.g. ['income-statement', 'health', 'insider'])",
- "items": {
- "type": "string"
- },
- "type": "array"
-}Input schema / properties / tickers / descriptionPrevious value: -"Array of ticker symbols"New value: +"Comma-separated ticker symbols (e.g. AAPL,MSFT,GOOGL)"Input schema / properties / tickers / itemsRemoved value: -{
- "type": "string"
-}Input schema / properties / tickers / typePrevious value: -"array"New value: +"string"Input schema / requiredPrevious value: -[
- "tickers",
- "endpoints"
-]New value: +[
+ "tickers"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It mentions efficiency but fails to disclose limits, result format, read-only nature, or any constraints beyond the schema.
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 but overly terse—a single sentence with no structure (title, sections). While short, it omissions reduce its usefulness.
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 simple input (one parameter, no output schema), the description should clarify what the batch query returns. It does not, leaving a crucial gap in completeness.
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 the single parameter 'tickers' with a description and example. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
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 'Batch query multiple tickers at once for efficiency' indicates batching and efficiency, but 'query' is vague—it doesn't specify what data is retrieved. It distinguishes from single-ticker siblings but lacks precision.
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 individual queries or get_all_financial_data. The description implies batching for efficiency but provides no explicit context or trade-offs.
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 tool groups have overlapping purposes: fda_drug_labels vs health_drug_search, fda_recalls vs health_recalls, fx_official_rates vs treasury_fx_rates, treasury_debt vs us_debt_current, and get_gdp vs get_bea_gdp. These near-duplicates create real ambiguity for an agent deciding which tool to call.
Names mix verb-led styles (get_, search_, compare_, screen_) with domain-led styles (fx_, treasury_, uk_, health_, eurostat_, datausa_). Within the same domain, similar actions use different patterns (get_gdp vs eurostat_gdp vs imf_indicator), making the set feel inconsistent and hard to predict.
75 tools is extreme for any MCP server, especially when many tools are redundant or cover unrelated domains (weather, earthquakes, scholarly search, air quality) outside the stated SEC/economics/demographics/FX focus. This overwhelms agents and burdens context windows.
Core domains like SEC financials, major economic indicators, basic demographics, and current FX rates are well covered. However, gaps remain: no historical FX rates, no stock price/quote tool, limited demographic breakdowns, and no ability to fetch full SEC filing text. Some operations end in dead ends.