get_funded_byGet the address that first funded a given address (the source of its initial funds).
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Account address to trace funding for. | |
| chainid | No | Numeric chain id (e.g. 1=Ethereum, 56=BNB, 137=Polygon). Defaults to server config. |
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 establish that the tool is read-only, idempotent, and non-destructive. The description adds the 'first funded' temporal scoping and clarifies that the result is an address, not a transaction list. It does not mention edge cases like missing funding history, but the safety profile is fully covered.
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?
The definition is a single, waste-free sentence that front-loads the verb and the result concept. Every word 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?
With only two parameters, complete schema documentation, and read-only/idempotent annotations, the tool is easy to invoke correctly. The lack of an output schema is mitigated by the description stating the output is an address, though edge cases are not discussed.
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 coverage is 100%: both address and chainid already include validation patterns and descriptive text. The description does not add parameter-specific detail beyond saying the address is the one to trace, so the schema carries the burden.
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 is specific: it names the operation (get), the resource (an address), and the precise result (the address that first funded it). This clearly distinguishes it from siblings like get_transactions or get_contract_creation by focusing on the initial funding source.
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 use case is clear: given an address, return the source of its initial funds. It does not explicitly name alternatives or exclusions, but among the many get_* siblings its purpose is unique enough that an agent can infer when to call it.
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.