USE THIS to verify an Ethereum address before sending funds or storing it — never trust that a 0x… string is correct. Validates the format and the EIP-55 mixed-case checksum (catches typos), and returns the correctly-checksummed form. A wrong character makes a different address — funds sent there are lost.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | The Ethereum address (0x + 40 hex chars). |
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 indicate readOnlyHint=true, and description adds important behavioral context: validates format and checksum, returns checksummed form, and warns about permanent fund loss for incorrect addresses. No contradictions.
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?
Three sentences, no fluff. First sentence gives imperative usage, second explains functionality, third warns of risk. Every sentence contributes meaning.
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 tool with read-only annotations, the description covers purpose, usage context, behavioral details, and risk. No gaps given complexity and no output schema needed.
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?
Schema has 100% coverage with a single parameter described. Description adds value beyond schema by explaining why validation matters ('never trust...') and the consequence of errors, aiding understanding beyond the field description.
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?
Description clearly states the tool validates Ethereum address format and EIP-55 checksum, and returns the correctly-checksummed form. It uses a specific verb ('validate') and resource ('Ethereum address'), and is easily distinguished from sibling validation 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?
Explicitly advises when to use the tool: 'before sending funds or storing it'. It warns against trusting raw strings, providing clear context. No explicit when-not-to-use, but sibling tools cover different validation types, so exclusion is implicit.
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.
Each tool targets a specific identifier or operation (e.g., validate_iban, parse_date, is_holiday). Even similar tools like validate_isbn and validate_isbn10 are distinct by version. There is no overlap or ambiguity.
Most tools follow a verb_noun pattern (validate_xxx, parse_xxx, format_currency). The exception is 'next_holiday', which uses an adjective instead of a verb. Otherwise consistent.
With 47 tools, the set is very large. While each tool is distinct, the count exceeds the recommended range (25+ is considered too many) and may overwhelm users or agents.
Covers a wide array of international identifiers and utilities, but notable gaps exist (e.g., no Canada SIN, India PAN, Mexico CURP). The set is broad but not exhaustive for the domain of data validation.