fear_greed_indexCurrent Fear & Greed index value and historical trend.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Current index, 0 (extreme fear) to 100 (extreme greed) | |
| history | No | Recent trend of the index | |
| updatedAt | No | ||
| classification | Yes | Label, e.g. `Greed`, `Neutral`, `Extreme Fear` |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "properties": {
+ "classification": {
+ "description": "Label, e.g. `Greed`, `Neutral`, `Extreme Fear`",
+ "type": "string"
+ },
+ "history": {
+ "description": "Recent trend of the index",
+ "items": {
+ "additionalProperties": true,
+ "properties": {
+ "timestamp": {
+ "description": "ISO-8601 timestamp of the data point",
+ "type": "string"
+ },
+ "value": {
+ "description": "The recorded numeric value",
+ "type": "number"
+ }
+ },
+ "required": [
+ "timestamp",
+ "value"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "updatedAt": {
+ "type": "string"
+ },
+ "value": {
+ "description": "Current index, 0 (extreme fear) to 100 (extreme greed)",
+ "maximum": 100,
+ "minimum": 0,
+ "type": "integer"
+ }
+ },
+ "required": [
+ "value",
+ "classification"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description's mention of 'current' and 'historical' adds limited value. It does not detail behaviors like data source or update frequency, which would be helpful beyond 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?
The description is a single concise sentence, appropriately sized for a simple tool. It front-loads the key information, though it could benefit from a minor structural improvement (e.g., separating current and historical aspects). Still, it is efficient.
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 is parameterless, has comprehensive annotations, and an output schema exists to detail the return value, the description is nearly complete. It covers the essential purpose. A slight gap is the lack of mention of data resolution or period, but this is minor.
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 tool has zero parameters and schema description coverage is 100% (trivially). Per guidelines, baseline is 4 for 0 params. The description adds no parameter information, but none is needed.
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 the 'current value and historical trend' of the Fear & Greed index, which is a specific verb+resource combination. It distinguishes itself from siblings like 'market_summary' and 'get_price' by focusing on a distinct market sentiment metric.
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 implies the tool is for general market sentiment, and siblings suggest alternatives for specific coin data, but no explicit when-to-use or when-not-to-use guidance is provided. The agent must infer context from sibling names.
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.