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Search AI Automation Agencies

search_agencies
Read-onlyIdempotent

Search the AI Agent Index for AI automation agencies (services firms that build AI solutions for clients). Filter by service type, industry, tools, or region.

Input Schema

NameRequiredDescriptionDefault
toolNoTool or platform specialization e.g. openai, anthropic, langchain, make, n8n, zapier
limitNoNumber of results to return, max 20
queryNoFree text search across agency names and descriptions
regionNoRegion served e.g. North America, Europe, Global / Remote
serviceNoService tag: ai-agent-building, workflow-automation, ai-strategy, chatbot-development, custom-integrations, voice-agents, rag-development, data-pipeline, prompt-engineering, ai-training
industryNoIndustry served e.g. SaaS, Finance, Healthcare, Manufacturing

Output Schema

NameRequiredDescriptionDefault
countYesNumber of agencies returned
agenciesYesArray of matching agencies

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint, and openWorldHint, so the safety profile is covered. The description adds useful domain scope and entity definition, but it does not describe matching behavior, result ordering, or other behavioral traits beyond what the structured fields provide.

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 compact sentence with a useful parenthetical definition, and the core purpose is front-loaded. Every part earns its place.

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

Completeness4/5

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

With an output schema present, read-only annotations, and complete parameter descriptions, the description is sufficient for an agent to invoke the tool correctly. The main gap is that it does not help the agent choose between this and sibling tools like search_agents or get_agency.

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 all six parameters are already documented in the schema. The description echoes four key filter dimensions but adds no syntax, enum, or default details beyond the schema, making the baseline 3 appropriate.

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 states a clear verb and resource: search the AI Agent Index for AI automation agencies, and it defines the entity as services firms that build AI solutions for clients. It does not explicitly distinguish this tool from sibling tools such as search_agents or get_agency, which keeps it from a 5.

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

Usage Guidelines3/5

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

The description implies usage by saying the tool can filter by service type, industry, tools, or region. However, it gives no explicit guidance on when to use this versus search_agents or get_agency, and no when-not conditions.

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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