Fetch the current Base mainnet block number from redundant public RPCs and return structured JSON with source and freshness metadata. $0.002/call via x402.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full disclosure burden. It adds meaningful behavioral detail: data is fetched from redundant public RPCs, results include source and freshness metadata, and each call costs $0.002 via x402. It does not enumerate failure modes or rate limits, but this is a simple read-only fetch and the disclosed information is sufficient.
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 two concise sentences with no filler. The action and resource are front-loaded, and the pricing detail is appended as an efficient second sentence.
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 zero-parameter read-only fetch, the description supplies enough: purpose, data source, return nature, and cost. It does not specify exact JSON field names, and there is no output schema, so a bit more detail about the returned structure could have improved it, but selection and invocation remain unambiguous.
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 the input schema is an empty object, so there is nothing for the description to clarify about parameter meanings. The baseline of 4 applies because the parameter surface is empty.
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 names a specific operation (fetch), resource (current Base mainnet block number), data source (redundant public RPCs), and output shape (structured JSON with source and freshness metadata). This makes it immediately distinguishable from sibling tools like base_gas_price and base_tx_status.
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 clearly establishes when the tool is appropriate: when the current Base mainnet block number is needed. It does not explicitly list alternative tools or exclusion conditions, but the specificity of the resource provides clear selection context.
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 tool groups are nearly indistinguishable: wallet_analyze, wallet_spy, and base_wallet_profile all inspect wallets; batch_extract, batch_url_json, and x401_batch_extract all batch-extract URLs; route_task, agentcore_route, and mpp_route all perform routing. An agent would need to read very carefully to avoid selecting the wrong tool.
All names are snake_case, but there is no consistent verb_noun or namespace pattern: many are noun-only (inference, echo, sentiment, server_time), some are prefixed by domain (bazaar_, base_, x402_, rep_), and action prefixes vary widely (fetch_, compile_, extract_, purchase_, route_). The naming is readable but not predictable across the set.
Seventy tools is an extremely large surface for an agent to choose from, and most appear to be independent paid service wrappers. This exceeds the 50+ extreme mismatch threshold in the calibration and creates an overwhelming selection problem.
Relative to its apparent purpose—exposing x402 payments and Bazaar market data—the coverage is extensive: diagnostics, preflight, settlement verification, receipt lookup, wallet checks, Bazaar analytics, web extraction, and text processing are all represented. The main gaps are operational side-effects like creating or updating a Bazaar listing, but those appear to be outside this read/purchase surface.