Base Wallet Balance ($0.001 USDC)
base_balanceRead native ETH and Circle USDC balances plus current block height for a Base wallet.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
base_balanceRead native ETH and Circle USDC balances plus current block height for a Base wallet.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the specific data returned (ETH, USDC, block height) but does not disclose output formatting, error behavior, or chain/confirmation caveats; this is adequate but not rich.
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?
A single front-loaded sentence with no filler; every word adds semantic value.
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 read-only tool with one parameter and no output schema, the description states all returned data. It could add fee/cost details from the title or output formatting, but nothing essential is missing for correct invocation.
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 0% schema description coverage and a single address parameter, the description's mention of 'a Base wallet' gives the parameter real-world meaning. The regex in the schema handles format, so the combined information is sufficient.
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 uses a specific verb ('Read') and identifies the exact resource: native ETH and Circle USDC balances plus current block height for a Base wallet. This clearly distinguishes it from the unrelated sibling URL/merchant 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?
It clearly indicates this is the read-only balance/block-height lookup for Base addresses, which implies when it applies. It does not explicitly name alternatives or exclusions, but the siblings are unrelated, so the intended context is unambiguous.
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 pairs have heavily overlapping purposes: check_url vs verify_web_evidence vs batch_check_urls all verify public URLs, while merchant_snapshot vs merchant_audit and payment_guard vs treasury_preflight cover very similar ground. The descriptions clarify some differences, but an agent could easily select the wrong tool when names alone are ambiguous.
All names use snake_case and are readable, but there is no consistent structural pattern. Some start with verbs (check_url, verify_web_evidence), while others are noun compounds (merchant_audit, payment_guard), and batch_check_urls places the verb in the middle. The naming is understandable but not predictable across the set.
At 8 tools, the count is reasonable and within the ideal range for a focused utility server. However, a few tools are near-duplicates of others, so the set feels slightly less well-scoped than the count alone suggests.
For the apparent niche of web3 payment preflight, merchant evaluation, and URL verification, the surface covers the core workflows well. The main gap is the lack of a more granular transaction-history or payment-execution tool, but agents can likely complete their intended tasks without dead ends.