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Algorand MCP

Algorand MCP

by GoPlausible
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bigint_to_bytes

Convert BigInt values to byte arrays for Algorand blockchain operations, handling network-specific encoding requirements.

Instructions

Convert a BigInt to bytes

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "value": "<value>",
      "size": "<size>"
    },
    "name": "bigint_to_bytes"
  }
}

Input Schema

NameRequiredDescriptionDefault
valueYesBigInt value as a string to convert to bytes
sizeYesSize of the resulting byte array
networkNoAlgorand network to use (default: mainnet)
itemsPerPageNoNumber of items per page for paginated responses (default: 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.1.1

TDQS

C2.9/5.0
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 the conversion action but doesn't explain what 'bytes' means in this context (e.g., byte array format, endianness), error handling, or performance characteristics. For a data transformation tool with zero annotation coverage, this leaves significant gaps.

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 wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward conversion tool.

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 the lack of annotations and output schema, the description is incomplete. It doesn't explain the output format (e.g., byte array representation), error conditions, or why parameters like 'network' and 'itemsPerPage' are relevant to a BigInt conversion. For a tool with 4 parameters and no structured output documentation, more context is needed.

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%, so the schema fully documents all four parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't clarify the relationship between 'value' and 'size', or why 'network' and 'itemsPerPage' are included). Baseline 3 is appropriate when the schema does all the work.

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 tool's purpose: converting a BigInt to bytes. It uses specific verbs ('Convert') and identifies the resource ('BigInt'). However, it doesn't distinguish itself from sibling tools like 'bytes_to_bigint' (which performs the inverse operation), missing an opportunity for clearer differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. There's no mention of sibling tools (like 'bytes_to_bigint'), typical use cases, or prerequisites. The agent must infer usage from the tool name and parameters alone.

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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