get_token_infoGet token project details and social links for a contract: name, symbol, divisor, type, total supply, description, website, socials, price, etc.
| Name | Required | Description | Default |
|---|---|---|---|
| chainid | No | Numeric chain id (e.g. 1=Ethereum, 56=BNB, 137=Polygon). Defaults to server config. | |
| contractaddress | Yes | Token contract address. |
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, openWorldHint, idempotentHint, and non-destructive behavior, so safety is covered. The description adds the returned field set but does not disclose potential data sparsity, missing socials, price availability, or default chain behavior beyond the schema.
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 a clear field list and no filler words. It efficiently communicates the tool's purpose without restating schema or annotation content.
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 read-only metadata lookup with only two well-documented parameters and annotations covering safety, the description is largely sufficient. It could be improved by explicitly noting that price/socials may be absent, but the openWorldHint and 'etc.' provide acceptable openness.
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 description coverage is 100%, with both chainid and contractaddress described. The description adds no parameter-level detail beyond the schema, so the baseline 3 is appropriate.
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 names a specific verb ('Get') and resource ('token project details and social links for a contract') with an explicit field list. This clearly differentiates it from sibling tools like get_token_balances, get_token_top_holders, and get_token_transfers, which serve different purposes.
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 implies usage: when you need token metadata and social links rather than balances or transfers. However, it does not explicitly mention sibling alternatives or state when not to use this tool, leaving usage boundaries to be inferred from the field list.
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.
Most tools target clearly distinct data types: balances, transactions, logs, contracts, tokens, gas, and chains. The main confusion risk is between get_transaction_status, get_transaction_receipt_status, and get_transaction_receipt, which all relate to transaction outcomes and could be easily misselected.
Every tool follows the get_<object> or get_<object>_<qualifier> snake_case pattern. The naming is highly predictable and makes the tool purpose evident from the name alone.
20 tools is on the heavier side, approaching the upper bound for a coherent MCP server. However, given Etherscan's broad read-only domain—addresses, transactions, contracts, tokens, logs, and gas—the count is defensible even if it feels somewhat large.
The toolset covers the major Etherscan data-access patterns: balances, normal/internal transactions, receipts, token transfers, contract ABI/source/creation, logs, and gas. Obvious gaps like fetching a block by number/hash or listing transactions within a block are missing, but agents can accomplish most explorer workflows.