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Jake-loranger

Algorand MCP Server

fund_testnet

Fund Algorand testnet accounts using the official faucet to obtain test tokens for development and testing purposes.

Instructions

Fund an Algorand testnet account using the official faucet

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesAlgorand testnet address to fund

Implementation Reference

  • Handler for the 'fund_testnet' tool. Parses input arguments using Zod schema, dynamically imports node-fetch, sends POST to Algorand testnet faucet API to fund the address, handles response or error.
    case 'fund_testnet': {
        const parsed = FundTestnetArgsSchema.parse(args);
        try {
            // Use node-fetch for HTTP requests
            const fetch: typeof import('node-fetch') = (await import('node-fetch')).default;
            const faucetUrl = `https://bank.testnet.algorand.network/api/v2/accounts/${parsed.address}`;
            const response = await fetch(faucetUrl, { method: 'POST' });
            if (!response.ok) {
                throw new Error(`Faucet request failed: ${response.statusText}`);
            }
            const result = await response.json();
            return {
                content: [
                    {
                        type: 'text',
                        text: `Faucet request sent!\nStatus: ${result.message || 'Success'}\nCheck your account balance in a few seconds.`,
                    },
                ],
            };
        } catch (error) {
            return {
                content: [
                    {
                        type: 'text',
                        text: `Faucet funding failed: ${error}`,
                    },
                ],
                isError: true,
            };
        }
    }
  • Zod schema definition for 'fund_testnet' tool arguments: requires a string 'address'.
    // FundTestnet tool schema
    const FundTestnetArgsSchema = z.object({
        address: z.string(),
    });
  • src/index.ts:142-155 (registration)
    Tool registration in the TOOLS array, defining name, description, and inputSchema matching the Zod schema.
    {
        name: 'fund_testnet',
        description: 'Fund an Algorand testnet account using the official faucet',
        inputSchema: {
            type: 'object',
            properties: {
                address: {
                    type: 'string',
                    description: 'Algorand testnet address to fund',
                },
            },
            required: ['address'],
        },
    },
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the faucet source but lacks details on rate limits, success/failure conditions, amount funded, or any prerequisites (e.g., account must exist). This is inadequate for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste—front-loaded with the core action and resource. Every word earns its place without redundancy or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks behavioral details (e.g., what happens on success/failure, amount funded) and output expectations, which are critical for an agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the parameter 'address' documented in the schema. The description adds no additional parameter semantics beyond implying it's for a testnet address, which is already clear from the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('fund') and target resource ('an Algorand testnet account'), using the official faucet. It distinguishes itself from siblings like 'send_payment' or 'transfer_asset' by specifying the faucet-based funding mechanism for testnet accounts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying 'testnet account' and 'official faucet', indicating this is for test environments rather than mainnet. However, it does not explicitly state when not to use it or name alternatives like 'send_payment' for peer-to-peer transfers, leaving some guidance gaps.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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