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Jake-loranger

Algorand MCP Server

get_account_info

Retrieve Algorand account details such as balance and asset holdings by providing the account address.

Instructions

Get account information including balance and assets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesAlgorand account address

Implementation Reference

  • MCP tool handler for 'get_account_info': parses arguments using Zod schema, calls algorandService.getAccountInfo, formats and returns the response.
    case 'get_account_info': {
        const parsed = GetAccountInfoArgsSchema.parse(args);
        try {
            const accountInfo = await algorandService.getAccountInfo(parsed.address);
            return {
                content: [
                    {
                        type: 'text',
                        text: `Account Information for ${parsed.address}:\n` +
                            `Balance: ${Number(accountInfo.balance) / 1000000} ALGO\n` +
                            `Minimum Balance: ${Number(accountInfo.minBalance) / 1000000} ALGO\n` +
                            `Status: ${accountInfo.status}\n` +
                            `Assets: ${accountInfo.assets.length}\n` +
                            `Created Apps: ${accountInfo.createdApps.length}\n` +
                            `Created Assets: ${accountInfo.createdAssets.length}`,
                    },
                ],
            };
        } catch (error) {
            return {
                content: [
                    {
                        type: 'text',
                        text: `Error getting account info: ${error}`,
                    },
                ],
                isError: true,
            };
        }
    }
  • Zod schema defining input validation for the tool: requires 'address' as string.
    const GetAccountInfoArgsSchema = z.object({
        address: z.string(),
    });
  • src/index.ts:165-178 (registration)
    Tool registration in TOOLS array: defines name, description, and JSON input schema for MCP server.
    {
        name: 'get_account_info',
        description: 'Get account information including balance and assets',
        inputSchema: {
            type: 'object',
            properties: {
                address: {
                    type: 'string',
                    description: 'Algorand account address',
                },
            },
            required: ['address'],
        },
    },
  • Core implementation in AlgorandService: fetches account details from Algorand node via algodClient and formats the response.
    async getAccountInfo(address: string) {
        try {
            const accountInfo = await this.algodClient.accountInformation(address).do();
            return {
                address: accountInfo.address,
                balance: accountInfo.amount,
                minBalance: accountInfo.minBalance,
                status: accountInfo.status,
                assets: accountInfo.assets || [],
                appsLocalState: accountInfo.appsLocalState || [],
                createdApps: accountInfo.createdApps || [],
                createdAssets: accountInfo.createdAssets || []
            };
        } catch (error) {
            throw new Error(`Failed to get account info: ${error}`);
        }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'gets' information, implying a read-only operation, but doesn't specify if it requires authentication, rate limits, network access, or what happens with invalid addresses. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

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. It front-loads the purpose ('Get account information') and specifies key data points ('balance and assets'), making it easy to scan and understand quickly without 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 no annotations, no output schema, and a simple single-parameter input, the description is incomplete. It doesn't cover behavioral aspects like safety, performance, or error handling, and lacks details on return values (e.g., format of balance and assets). For a tool interacting with account data, more context is needed to ensure proper usage.

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?

The input schema has 100% description coverage, with the 'address' parameter fully documented as an 'Algorand account address'. The description adds no additional parameter details beyond implying it retrieves 'account information' for that address. Baseline 3 is appropriate since the schema does the heavy lifting, but the description doesn't enhance parameter understanding.

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

Purpose4/5

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

The description clearly states the verb ('Get') and resource ('account information'), specifying what data is retrieved ('balance and assets'). It distinguishes from siblings like 'get_asset_info' (specific asset) or 'generate_algorand_account' (creation). However, it doesn't explicitly differentiate from 'load_wallet' or 'store_wallet', which might involve account data but with different operations.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an account address), exclusions, or comparisons to siblings like 'get_asset_info' for asset-specific details or 'load_wallet' for wallet-based access. The description implies usage for retrieving account data but lacks contextual direction.

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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