transactionsFetch recent Bitstamp trades for a currency pair; optional time filter (minute, hour, day) sets the lookback window. Returns trade id, price, amount, type, and timestamp.
| Name | Required | Description | Default |
|---|---|---|---|
| time | No | ||
| currency_pair | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| transactions | No | List of recent transactions |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "currency_pair": "btcusd"
+ },
+ {
+ "currency_pair": "ethusd",
+ "time": "hour"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "transactions": {
+ "description": "List of recent transactions",
+ "items": {
+ "properties": {
+ "amount": {
+ "description": "Transaction amount",
+ "type": "string"
+ },
+ "date": {
+ "description": "Transaction date",
+ "type": "string"
+ },
+ "price": {
+ "description": "Transaction price",
+ "type": "string"
+ },
+ "tid": {
+ "description": "Transaction ID",
+ "type": "string"
+ },
+ "type": {
+ "description": "Buy or sell",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as read-only and idempotent, so the safety profile is covered. The description adds valuable context by explaining the time parameter as a lookback window (minute, hour, day) and listing the return fields (trade id, price, amount, type, timestamp), which goes beyond the annotations. It does not mention pagination or result limits, but the output schema exists.
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 sentences, no redundant phrasing. The first sentence states the core purpose and scope; the second clarifies the optional parameter and return fields. Every word earns its place.
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?
For a simple two-parameter tool with an output schema and full annotations, the description provides everything needed for selection and invocation: what it does, what the parameters mean, and what to expect in the response. No significant gaps.
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 0%, so the description carries the burden; it explains both parameters: 'currency pair' is the trading pair, and 'time' is an optional filter with specific values (minute, hour, day) defining the lookback window. The schema examples reinforce the format (e.g., 'btcusd'), making this sufficient.
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 starts with 'Fetch recent Bitstamp trades for a currency pair,' a specific verb-resource pair that clearly distinguishes this from siblings like order_book (current orders) or ticker (price). It also scopes the tool to trades for a currency pair, leaving no ambiguity.
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 retrieving recent trade history, which is a clear context. It does not explicitly compare with alternatives (e.g., 'for real-time prices use ticker'), but the optional time filter gives a sense of when to use the tool for custom lookbacks. No misleading guidance.
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 heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions, while the polymarket_edges, polymarket_arbitrage, and related tools blur edge-detection boundaries. The server's Bitstamp identity also clashes with the bulk of tools being unrelated data-research, making selection harder.
Tool names are all lowercase snake_case, which is consistent formatting, but no coherent verb_noun pattern emerges. Some are verb-first (ask_pipeworx, compare_entities, discover_tools) while others are noun-first or resource-based (ticker_hour, order_book, polymarket_edges), and the naming style differs across the two major domains.
At 38 tools, the set is well over the 15-tool threshold for a focused server, and the majority of tools are unrelated to the server's Bitstamp name. The count feels bloated and scattershot—it would be better split into separate data-research and exchange servers.
The data-research and question-answering surface is broadly covered, with meta-tools and validation. However, the Bitstamp exchange half is incomplete: it only provides public market data (ticker, order book, trades, OHLC) with no trading, account, or private-data operations, an obvious gap given the server's name.