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zyndai-mcp-server

by zyndai

Search AgentDNS

zyndai_search_agents
Read-onlyIdempotent

Search the AgentDNS network for agents and services using semantic and keyword queries. Filter results by category, tags, status, and more to find exactly what you need.

Instructions

Search the AgentDNS network for agents and services.

Hits the registry's hybrid search (semantic + keyword) at POST /v1/search. Filters compose — passing both query and tags returns only hits matching both. Omit query and pass only filters to browse the network.

Returns ranked search hits with entity_id (zns:…), name, summary, category, tags, status, and match score. Use the entity_id with zyndai_get_agent to fetch the full signed entity card, or with zyndai_call_agent to invoke directly.

Examples:

  • "Find agents that analyze stocks" -> { query: "stock analysis" }

  • "List all finance agents" -> { category: "finance" }

  • "Find LangChain agents in Spanish" -> { tags: ["langchain"], languages: ["es"] }

  • "Browse with full cards" -> { enrich: true }

  • "Federated search across registries" -> { query: "translation", federated: true }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFilter by tags. Examples: ['langchain', 'multi-agent'], ['nlp', 'translation'].
queryNoNatural-language search query. Examples: 'stock analysis', 'pdf summarizer', 'spanish translator'. Omit to browse the registry by filters only.
enrichNoIf true, the registry hydrates each hit with its full entity card (more bytes, but saves a follow-up zyndai_get_agent call).
modelsNoFilter by underlying LLM model. Examples: ['gpt-4o-mini'], ['claude-sonnet'].
offsetNoSkip N results — pagination.
skillsNoFilter by declared skills.
statusNoFilter by entity status (default: online).
categoryNoFilter by category (e.g. 'finance', 'productivity', 'general'). Use the zyndai_resolve_fqan tool to discover categories.
federatedNoIf true, query peer registries in the federation in addition to the configured one.
languagesNoFilter by spoken/text language(s). ISO codes — examples: ['en', 'es', 'ja'].
protocolsNoFilter by communication protocol. Examples: ['http'] (most common), ['mqtt'].
max_resultsNoMax results 1-100 (default 10).
min_trust_scoreNoMinimum registry trust score (0–1).
Behavior5/5

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

The description goes beyond the annotations by detailing the underlying API endpoint (POST /v1/search), the hybrid search mechanism, filter composition behavior, and the returned fields. No contradictions with annotations.

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 well-structured: it begins with the purpose, then provides technical details, return format, and usage examples. Every sentence adds value, and the length is appropriate for the tool's complexity.

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

Completeness5/5

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

Given the 13 parameters, no output schema, and the presence of sibling tools, the description is complete. It covers behavior, return fields, provides examples, and links to related tools. No major gaps.

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

Parameters5/5

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

With 100% schema description coverage, the baseline is 3. However, the description adds significant meaning through examples for each parameter (e.g., query, category, tags, enrich, federated) and explains how filters combine. This greatly aids the agent in selecting appropriate parameters.

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 tool's purpose: 'Search the AgentDNS network for agents and services.' It uses a specific verb (search) and resource, and distinguishes from sibling tools by mentioning hybrid search, filters, and the ability to browse without a query.

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 provides explicit guidance on when to use the tool (e.g., 'Omit `query` and pass only filters to browse the network') and includes examples of various parameter combinations. It does not explicitly state when not to use it, but the context implies differentiation from siblings like zyndai_list_agents.

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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