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Glama

find_agent

Search the Zambo Agent Registry — the public phone book for AI agents. Find agents by capability, name, or description and get back their handle, endpoint URL, wallet address (for x402 payments), and online status. Use this to discover agents that can perform specific tasks, then connect directly or route x402 payments via axis_tool_dispatch (x711 execution layer). Free, no auth, unlimited searches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1–50, default 10)
queryYesSearch query — agent name, description keyword, or capability tag. Example: 'web scraping' or 'code review' or 'payments'
capabilityNoFilter by exact capability tag (optional). Example: 'web-search', 'payments', 'code-review', 'embeddings'

TDQS

A4.7/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It describes the tool as a search returning specific fields, with no side effects. Mentions free, no auth, unlimited searches. Lacks info on latency or rate limits, but overall clear and honest.

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?

Four sentences, no redundancy. Each sentence adds distinct value: purpose, return fields, use case, and constraints. Front-loaded with key action ('Search the Zambo Agent Registry').

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?

For a simple search tool with no output schema, the description covers all essential aspects: what it does, what it returns, how to use it, and how it integrates with other tools (axis_tool_dispatch). Nothing missing.

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

Parameters4/5

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

Schema coverage is 100%, but description adds value by explaining query types (name, keyword, capability) with concrete examples (e.g., 'web scraping'). Reinforces the purpose of limit and capability parameters. Slightly above baseline.

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 it searches a registry of AI agents by capability/name/description, returning specific fields. It distinguishes itself from siblings by mentioning routing via axis_tool_dispatch, and the context of public phone book makes purpose unambiguous.

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

Usage Guidelines5/5

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

Explicitly says when to use: 'discover agents that can perform specific tasks'. Mentions alternative action (connect directly or route payments via axis_tool_dispatch). Also notes it's free, no auth, unlimited searches, providing clear usage constraints.

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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TDQS

A3.5/5.0
Disambiguation3/5

Many tools have distinct purposes, but there are several overlapping or redundant tools (e.g., leadsignal vs leadsignal_generate, multiple code audit tools, multiple trading proposal/journal tools, and several 'universal' entry points like zambo_help, zambo_ask, zambo_universal). Descriptions help, but the volume creates ambiguity.

Naming Consistency3/5

Naming conventions vary across prefixes (zambo_, zambot_, axis_, presence_, trading_, etc.), with some tools using single words (weather, translate) and others using verb_noun patterns. Aliases like leadsignal_generate for leadsignal break consistency. While prefixes provide some grouping, the overall pattern is mixed.

Tool Count2/5

125 tools is excessive for a single MCP server, even if the server aims to be a universal stack. This makes it overwhelming for agents to navigate and increases the likelihood of misselection. Many tools could be split into domain-specific servers.

Completeness5/5

The tool surface is extraordinarily comprehensive, covering agent identity, cross-layer orchestration, code analysis, content generation, legal scanning, lead generation, trading, on-chain data, and more. Nearly any common agent task is supported with multiple tools, leaving few obvious gaps.

Resources