resolve_symbols_batchResolve up to 100 symbols in a single request. Requires a plan with bulk endpoints enabled.
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | Source exchange or quote currency applied to every input symbol | |
| symbols | Yes | Up to 100 symbols to resolve in a single request |
| Name | Required | Description | Default |
|---|---|---|---|
| resolved | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / context / descriptionAdded value: +"Source exchange or quote currency applied to every input symbol"Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "properties": {
+ "resolved": {
+ "items": {
+ "additionalProperties": true,
+ "properties": {
+ "coinId": {
+ "description": "Canonical Bitcompare coin ID",
+ "type": "string"
+ },
+ "input": {
+ "description": "The raw symbol that was queried",
+ "type": "string"
+ },
+ "name": {
+ "description": "Coin display name",
+ "type": "string"
+ },
+ "symbol": {
+ "description": "Canonical symbol",
+ "type": "string"
+ }
+ },
+ "required": [
+ "input",
+ "coinId",
+ "symbol",
+ "name"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "resolved"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive nature, so the description adds value by specifying the batch limit (100 symbols) and plan requirement, without contradicting annotations.
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 concise sentences with no redundancy, front-loading the key purpose and limitations.
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 rich annotations and presence of an output schema, the description adequately covers the tool's behavior (batch limit, plan requirement). It could mention partial failure handling but is otherwise sufficient.
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 does not add new parameter information beyond what the schema already provides (e.g., context and symbols descriptions), so baseline score of 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 title 'Batch resolve symbols' and description 'Resolve up to 100 symbols in a single request' clearly specify the verb (resolve) and resource (symbols), distinguishing it from the sibling tool 'resolve_symbol' which handles single symbols.
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 mentions the prerequisite 'Requires a plan with bulk endpoints enabled' and implies batch usage via 'up to 100 symbols', but does not explicitly contrast with the single resolve tool or state when to prefer this tool.
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.
Each tool targets a distinct aspect of cryptocurrency data: coin metadata, prices, rates (current, historical, changes), earn products, market summaries, stablecoin analysis, and symbol resolution. The detailed descriptions clearly differentiate even similar tools like get_price and get_price_by_symbol, or get_rates and list_earn_products.
All names use snake_case, but conventions vary: some are verb_noun (get_coin, list_coins, resolve_symbol), some are noun_noun (coin_history, fear_greed_index, market_summary), and some include 'by' for parameters. This mix is readable but could be more consistent.
With 21 tools, the server covers a broad domain of cryptocurrency data without being overwhelming. Each tool serves a clear purpose, and the count is appropriate for a comprehensive data API.
The tool set covers nearly all expected operations for a crypto data server: coin listing, metadata, prices, historical data, rates, yield products, market stats, top coins, stablecoin analysis, and symbol resolution. No obvious gaps are present for the stated focus on price, rate, and yield data.