FX rates via Frankfurter (ECB). Req: { base?: string, symbols?: csv } (x402: 0.001 USDC per call)
HTTP equivalent: GET /x402/fx-rate Payment: x402 protocol — send X-PAYMENT header with base64 payment payload, or X-API-Key / X-Owner-Key / Bearer token to bypass.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide no read-only or destructive hints, so the description must disclose behavior. It does disclose the x402 payment requirement (0.001 USDC/call) and available auth methods, which is valuable. However, it stops short of describing response structure or rate limits.
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 compact and front-loaded. The first sentence states the purpose, and subsequent sentences cover parameters/cost, HTTP endpoint, and payment/auth—all essential and non-redundant.
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 tool with no output schema and minimal annotations, the description provides core invocation details: parameters, cost, endpoint, and authentication. It omits the response format, but that is largely self-evident for a rate lookup service.
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 input schema is empty, but the description introduces optional 'base' and 'symbols' parameters with a CSV format hint. This effectively compensates for the schema, though it lacks details like allowed currency codes or default behavior.
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 identifies the tool as providing FX rates from the European Central Bank via Frankfurter. This is specific and distinguishes it from crypto price tools in the sibling list, though it lacks an explicit verb like 'get'.
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 usage for fiat exchange rates by naming the ECB source, but it does not explicitly state when to prefer this over alternatives like crypto_price or coingecko tools, nor does it provide exclusion criteria.
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.
Multiple tool pairs are exact duplicates (e.g., wallet_analysis/wallet_analyzer, honeypot_check/rugpull_detector, defi_yield/defi_yield_rates) with identical descriptions, and many overlapping scanners (squeeze_scanner variants). An agent cannot reliably distinguish these tools.
Names are all snake_case, but conventions vary wildly: some are resource names (btc_price), some are actions (list_magnets), some are generic utilities (calculator), and duplicates use different naming patterns for the same function (wallet_analysis vs wallet_analyzer). No consistent verb_noun or resource_action pattern.
139 tools is an extreme count for any MCP server, far exceeding the 50+ threshold. The scope is a grab-bag of unrelated domains (crypto, FDA, SEC, utilities, web scraping), suggesting no curation.
The set is a shallow pile of read-only queries and utilities with no lifecycle management for any one domain. Many sub-areas have only one or two tools, and duplicates occupy slots where distinct operations should be. The lack of a clear domain makes completeness impossible to assess, but the surface is redundant rather than comprehensive.