Current Base mainnet gas price (wei/gwei), EIP-1559 base_fee_gwei/priority_fee_gwei, and gas_price_usd (ETH price cross-call — no price oracle on ETH-only competitors) via multi-provider JSON-RPC. Cost: $0.005 USDC per 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?
No annotations are provided, so the description carries full burden. It discloses the cost ($0.005 USDC per call) and data source (multi-provider JSON-RPC), but does not mention idempotency, rate limits, or caching behavior.
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 with no wasted words. Key information (outputs, cost, data source) is front-loaded.
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?
While the tool has no parameters and no output schema, the description does not specify the exact JSON response structure, which could help an agent parse the result correctly.
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?
With zero parameters and 100% schema coverage, baseline is 4. The description adds meaning by detailing the output fields (wei/gwei, base_fee_gwei, priority_fee_gwei, gas_price_usd) and the cross-call mechanism.
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 specifies the tool retrieves current Base mainnet gas prices in multiple units (wei/gwei, EIP-1559 fees, USD price) via multi-provider JSON-RPC, distinguishing it from preview tools.
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 mentions cost and differentiation from ETH-only competitors, but does not explicitly state when to use this tool versus alternatives like chain_gas_price_preview or other gas price tools.
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.
The tools are organized into clear families (chain, crypto, defi, pm, enrich, scan) and each targets a distinct data type. The preview tools are explicitly labeled as free samples, reducing but not eliminating confusion with their paid counterparts. Some overlap exists between chain_wallet and chain_balance, and between enrich_domain and enrich_tech_risk, but descriptions clarify the difference.
All tools follow a consistent resource_action pattern using snake_case (chain_balance, crypto_funding, enrich_domain). Preview tools consistently append '_preview' to their paid counterpart. The only minor variation is abbreviations like 'tx', 'pm', 'defi', but these are uniform.
At 22 tools, the server is on the heavy side. The eight preview tools duplicate the functionality of their paid versions and inflate the count, though they serve a legitimate 'try before pay' purpose. The remaining 14 paid tools cover a wide range of risk data, making the count borderline appropriate.
The set covers on-chain balances, token security, DeFi yields, crypto prices, funding rates, prediction markets, domain enrichment, tech-risk CVE scanning, and MCP server auditing, which is a comprehensive risk toolkit. Minor gaps exist (e.g., no historical data, no address reputation, no token price by address), but the core workflows are well covered.