gas now
gas_nowCurrent gas prices in Gwei for Base, Ethereum, or Arbitrum via public RPC. [free]
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | base (default), ethereum, or arbitrum |
ThirdMade Shelf
TDQS
B3.3/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It does add useful context: data is fetched via public RPC, prices are in Gwei, and the tool is free. However, it does not mention failure modes, rate limits, or reliability issues that might come with public endpoints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. The '[free]' and 'via public RPC' markers convey useful extra information without bloating the text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter, read-only tool, the description covers most essentials: chains, unit, source, and cost. However, there is no output schema and no mention of the return shape, so an agent may not know exactly what to expect when parsing the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter 'chain' is fully documented in the schema with its allowed values and default. The description repeats the chain names and adds the unit 'Gwei', but it does not add meaningful parameter-level semantics beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the resource: current gas prices in Gwei for Base, Ethereum, or Arbitrum. It lacks an explicit verb like 'get' or 'fetch', and it does not contrast with sibling tools, but the purpose is unambiguous and specific enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives. The '[free]' and 'public RPC' notes imply a lightweight option, but there is no when-to-use or when-not-to-use statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
B3.2/5.0
Disambiguation3/5
Most tools have distinct purposes, but several clusters overlap: domain_facts, page_meta, and scrape all return page title information, and search_verify, hallucination_check, and sweep all target claim validation. The descriptions usually clarify the use case, but the boundaries are not always obvious.
Naming Consistency3/5
All names use lowercase snake_case, so there is a baseline consistency, but the pattern is mixed: bare verbs like scrape, summarize, and sweep sit alongside noun+noun forms like domain_facts and noun+verb forms like entity_find. The names are readable but do not form a predictable verb_noun API convention.
Tool Count3/5
At 26 tools, this is heavy and above the typical well-scoped 3-15 range, though the server is explicitly positioned as a broad shelf of paid utilities. Many tools are small one-purpose endpoints, so the count feels more like a catalog than a focused suite, but it is not an extreme mismatch.
Completeness4/5
The shelf covers the major advertised areas: web page analysis, research verification, text guards and NLP, blockchain reads, and image generation. There are some gaps such as no web search and no transaction sending, but agents can typically work around them or pair this with another server.