net-mcp

Rpki Roa Lookup

rpki_roa_lookup

Look up RPKI ROAs for a prefix or ASN to verify authorized route origins. Returns matching Route Origin Authorizations with max-length, trust anchor, and ASN from RIPEstat.

Instructions

Look up RPKI ROAs for a prefix or ASN.

Returns Route Origin Authorizations matching the query, including max-length, trust anchor, and ASN. Useful for understanding what routes an AS is authorized to originate or what ROAs cover a prefix.

For an ASN query only the first 50 announced prefixes are scanned (large ASes announce thousands); note says when that cap applied. Data source: RIPEstat. error is set if RIPEstat could not be reached.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	Prefix in CIDR notation (e.g. '1.1.1.0/24') or ASN as integer (e.g. '13335') to look up ROAs for

Output Schema

TableJSON Schema

Name	Required	Description
`note`	No	Set when results were truncated or partial
`roas`	Yes	Matching ROAs
`error`	No	Set when an upstream lookup failed; other fields may be empty or partial.
`query`	Yes	The prefix or ASN that was queried
`total`	Yes	Number of ROAs returned

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 22, 2026

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations, the description carries full responsibility for behavior. It discloses the 50-prefix scan cap for ASN queries, the `note` field indicating when the cap applied, the RIPEstat data source, and the `error` field when RIPEstat is unreachable. These are meaningful behavioral traits beyond the schema.

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 concise and well-structured: purpose first, then return values and use cases, then important limitations and data source. Every sentence carries useful information without padding.

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 single-parameter lookup with an output schema, the description covers purpose, query types, return fields, use cases, a cap behavior, and error conditions. Nothing essential is missing for an agent to invoke it correctly.

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 coverage is 100% and the query parameter description in the schema already explains prefix CIDR and ASN integer formats. The description mostly reinforces this rather than adding new parameter-specific meaning, so the baseline of 3 applies.

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 states a specific verb and resource: 'Look up RPKI ROAs for a prefix or ASN.' It also names what is returned (matching ROAs with max-length, trust anchor, ASN), making the tool's scope clear and distinguishable from siblings like rpki_validate or rpki_aspa_lookup.

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 clear use cases: 'understanding what routes an AS is authorized to originate or what ROAs cover a prefix.' It does not explicitly name alternatives or state when not to use, but the context is clear enough.

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