agentweb-mcp

get_business

Retrieve business details using a slug or UUID. Returns markdown prose for compact, LLM-friendly output, or JSON for structured data.

Instructions

Fetch a single business by slug or UUID. Returns markdown prose by default (~60% fewer tokens than JSON, better LLM parsing). Slugs look like 'noma-copenhagen-abc12345' — human-readable, shareable URLs. Use this when you already have an identifier from a previous search. Set format='json' if you need structured data.

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": {
      "id": "<id>"
    },
    "name": "get_business"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	The business slug (e.g. 'noma-copenhagen-abc12345') or UUID from AgentWeb. Slugs are preferred — they appear in search results and are shareable.
`format`	No	Response format. 'text' (default) returns markdown prose. 'json' returns structured JSON.	text

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.17.0Jun 21, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Discloses default response format (markdown) with token savings, and explains slug structure. No contradictions; read-only tool with adequate transparency for its scope.

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?

Two information-dense sentences, front-loaded with core action. No wasted words.

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 fetch tool with 2 parameters and no output schema, the description fully covers use cases, identifier types, and format implications.

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%, baseline 3. Description adds value: explains slug format, preference over UUID, and format option context beyond enum.

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?

Specific verb 'Fetch' and resource 'single business' with clear identifier types (slug/UUID). Distinguishes from sibling tools like search_businesses and batch_get_businesses.

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 'Use this when you already have an identifier from a previous search', implying not for discovery. Also gives guidance on when to use format='json'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.