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Algorand MCP

Algorand MCP

by GoPlausible
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TypeScript
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api_nfd_search_nfds

Search Algorand blockchain NFDs using filters like name, category, price range, sale type, and ownership status to find specific digital assets.

Instructions

Search NFDs with various filters

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "api_nfd_search_nfds"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNoName to search for
categoryNo
saleTypeNo
stateNo
ownerNoOwner address to filter on
minPriceNoMinimum price
maxPriceNoMaximum price
limitNoLimit the number of results
offsetNoOffset for pagination
sortNoSort order
viewNoView of data to return
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

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'various filters' but doesn't disclose critical behaviors: whether this is a read-only operation, if it has rate limits, authentication requirements, pagination details beyond offset/limit parameters, error conditions, or response format. For a search tool with 13 parameters, this is insufficient.

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

Conciseness4/5

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

The description is a single, efficient sentence with no wasted words. However, it's overly terse for a tool with 13 parameters and no annotations, potentially sacrificing clarity for brevity. It's front-loaded but under-specified.

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?

For a complex search tool with 13 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what NFDs are, how results are structured, pagination behavior, error handling, or network implications. The context signals indicate high complexity, but the description fails to provide necessary operational context.

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 77%, providing good baseline documentation. The description adds minimal value by mentioning 'various filters', which loosely references the parameters but doesn't explain their relationships, default behaviors, or practical usage examples. It compensates slightly but doesn't fully address the 23% coverage gap.

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

Purpose3/5

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

The description 'Search NFDs with various filters' clearly states the action (search) and target resource (NFDs), but it's vague about what NFDs are (likely Non-Fungible Domains on Algorand) and doesn't differentiate from sibling tools like 'api_nfd_browse_nfds' or 'api_nfd_get_nfd'. It provides basic purpose but lacks specificity and sibling distinction.

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 offers no guidance on when to use this tool versus alternatives. With siblings like 'api_nfd_browse_nfds' and 'api_nfd_get_nfd' available, there's no indication of differences in scope, filtering capabilities, or performance. Users must infer usage from the name 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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