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Artirain

nodemaven-mcp

by Artirain

nodemaven_list_locations

Read-onlyIdempotent

Discover exact country, region, city, ISP, or zip code names for proxy targeting. Prevents empty proxy pools by verifying spellings before use.

Instructions

List the countries, regions, cities, ISPs or zip codes available for targeting.

Use this to discover exact spellings before targeting - guessing a city name is the most common reason a proxy connection returns an empty pool.

Returns: str: Markdown or JSON with the schema: { "total": int, "count": int, "offset": int, "limit": int, "has_more": bool, "next_offset": int | None, "items": [ { ... } ] # raw records as returned by NodeMaven } On failure: "Error: "

Examples: - "which countries can I target?" -> level='countries' - "list German cities" -> level='cities', country='de' - "which carriers exist in the US?" -> level='isps', country='us'

Requires NODEMAVEN_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelNoOne of: countries, regions, cities, isps, zipcodes.countries
limitNoMaximum records to return.
offsetNoRecords to skip, for pagination.
regionNoRegion name scoping cities.
countryNoTwo-letter country code scoping regions, cities, ISPs or zip codes.
response_formatNo'markdown' for a compact summary, 'json' for the full payload.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description adds substantial behavioral context beyond annotations: the exact return structure (Markdown/JSON with schema), failure format ('Error: ...'), API key requirement, and the practical consequence of incorrect spellings. It does not contradict the read-only/idempotent 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 and front-loaded with the core purpose. It flowssections for usage guidance, return schema, examples, and requirement, with no redundant sentences. 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?

For a discovery tool with six optional parameters and an output schema, the description is complete: it covers purpose, when to use, return format, error handling, API key requirement, and provides examples. The schema covers parameter details, so no important gaps remain.

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%, so the baseline is 3. The description enriches parameter understanding with examples like 'list German cities' -> level='cities', country='de', and mentions response_format implicitly via 'Markdown or JSON'. This adds value beyond the schema's individual parameter descriptions.

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 that the tool lists available targeting locations (countries, regions, cities, ISPs, zip codes), using a specific verb and resource. It also distinguishes itself from sibling tools by its focus on location discovery before targeting.

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?

It explicitly says to use this tool to discover exact spellings before targeting and warns against guessing, which causes empty pools. It provides concrete examples mapping intents to parameter values. However, it does not explicitly mention when not to use it or compare with alternative tools, so it falls just short of a 5.

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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