Finance Signal Bundle - get live computed signal: BTC MVRV (market cap / realized cap) from BGeometrics, lagged only 1 day. MVRV<1 deep undervaluation (buy zone), >3.5 bubble top. Cycle-leve Price 0.01 via x402 (USDC on Base).
| Name | Required | Description | Default |
|---|---|---|---|
| wallet | No | optional 0x wallet for X-Wallet free tier (free credits every month: 100 anonymous or 5000 with a bound wallet) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses useful behavioral traits: the data is lagged 1 day, sourced from BGeometrics, and computed live. It also attempts to disclose a fee ('Price 0.01 via x402 (USDC on Base)'), but the phrase is confusingly worded with a typo ('Cycle-leve'), obscuring the actual payment mechanism. No annotations are present, so this limited disclosure carries full weight, but the ambiguity prevents a higher score.
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 relatively compact, but it contains a typo ('Cycle-leve') and an unclear clause that requires interpretation. The three-sentence structure is front-loaded with the core signal, but the final sentence's wording detracts from overall clarity.
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 one-parameter signal tool, the description covers the key elements: metric definition, source, latency, interpretation thresholds, and a pricing hint. However, it does not describe the return value shape or what 'Finance Signal Bundle' includes, and the payment detail is garbled, leaving some gaps in the absence of an output schema and annotations.
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 already fully describes the only parameter (wallet) with a clear explanation of its free-tier benefit. The description adds no parameter-level semantic nuance, so the baseline 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 description clearly states the tool's function: getting the live computed BTC MVRV (market cap / realized cap) signal from BGeometrics with a 1-day lag. It specifies the exact metric and interpretive thresholds, distinguishing it from the many sibling processed_* and signal_* tools. The verb 'get' and resource 'BTC MVRV signal' are specific and unambiguous.
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 thresholds (MVRV<1 buy zone, >3.5 bubble top) provide concrete context for when this signal is actionable, implying its use as a BTC valuation/cycle indicator. However, it does not explicitly name alternative tools or scenarios where a different signal would be preferred, so it falls short of a 5.
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.
Nearly all 80+ processed_/signal_ tools share the same boilerplate description and overlapping coverage areas (e.g., processed_global_markets vs. processed_global_indices vs. signal_global_indices; processed_crypto_funding_rate vs. processed_crypto_funding_rates), so an agent cannot reliably distinguish them. The generic ai_gateway, fetch_data, and list_products also have somewhat fuzzy boundaries around data access. Only broad asset categories in the names provide any separation.
Core tools use verb-first imperative names (fetch_data, get_product_info, list_products), while the vast majority use adjective/noun prefixes (processed_*, signal_*), so the set mixes conventions. Within each cluster naming is consistent and all names are readable snake_case, but the 87-tool surface has no single predictable verb_noun pattern. Minor singular/plural inconsistencies like processed_crypto_funding_rate vs. processed_crypto_funding_rates add friction.
87 tools is an extremely large surface for an MCP server, and most are variant data products that could be one fetch_data call with a product identifier. This falls into the >50 extreme range. The generic list/get/fetch primitives make the 80+ product-specific endpoints especially redundant.
The core consumer flow is covered: list products, inspect product info, and fetch a product (with payment challenge handling). Missing wallet/credit/balance tools and search/filtering are notable but work-aroundable. For a read-only data marketplace the lifecycle is largely complete.