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Glama

Abuseipdb

by io.github.pipeworx-io

Check Ip

check_ip
Read-onlyIdempotent

Check an IP address against the AbuseIPDB database. Returns abuse confidence score (0-100), ISP, usage type, country, number of reports, and last reported date. Example: check_ip("8.8.8.8").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipYesIPv4 or IPv6 address to check (e.g., "118.25.6.39")
_apiKeyYesAbuseIPDB API key

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipYesThe IP address checked
ispYesInternet Service Provider name
domainYesAssociated domain name
is_publicYesWhether the IP is public
usage_typeYesType of IP usage (e.g., Commercial, Residential)
country_codeYesCountry code of the IP
total_reportsYesTotal number of abuse reports for this IP
last_reported_atYesISO timestamp of last abuse report, or null
abuse_confidence_scoreYesAbuse confidence score from 0-100

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. The description adds the AbuseIPDB external service context and the 0-100 score scale, which is helpful but not extensive. No contradiction with 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?

Two concise sentences plus an illustrative example. The first sentence front-loads the purpose, and every part earns its place with no redundant text.

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?

The tool is simple, has output schema, and strong annotations. The description covers purpose, example, and key return fields. Could mention API key requirement explicitly, but the example covers it.

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 covers 100% of parameters with descriptions. The description's example adds a realistic invocation pattern with placeholder API key and example IP, but does not add meaning beyond the schema.

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 clearly states the tool checks an IP against AbuseIPDB and lists the returned data. It does not explicitly differentiate from sibling report_ip, but the verb 'check' implies a read-only lookup distinct from reporting.

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 a concrete example of how to call the tool with an API key, which demonstrates usage. It doesn't explicitly state when to use this over alternatives like report_ip, but the read-only context is clear.

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

All Abuseipdb toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are explicitly identical in current behavior, ai_visibility_check is subsumed by scan_competitor_ai_presence, and the six Polymarket-related tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) blur together. An agent would struggle to pick the right tool without reading the very long descriptions in full.

Naming Consistency2/5

Naming conventions are mixed: verb_noun (check_ip, get_blacklist, report_ip), bare nouns (entity_profile, deep_research, bet_research), prefix families (ask_pipeworx*, polymarket_*, pipeworx_*), and standalone verbs (remember, recall, forget, subscribe). The server itself is named Abuseipdb but the vast majority of tools are Pipeworx-related, making the naming feel disconnected from the server identity.

Tool Count2/5

At 34 tools, this exceeds the 25+ threshold for a heavy tool surface. The set is a grab bag of unrelated domains—AbuseIPDB, Pipeworx data access, Polymarket betting, memory management, AI visibility, dependency scanning, and llms.txt generation—rather than a cohesive single-purpose server. Many meta-tools (suggest_questions, discover_tools, pipeworx_trending, pipeworx_feedback) further inflate the count.

Completeness3/5

The de facto Pipeworx data-access domain is well covered with router, grounded, deep-research, entity, comparison, validation, resolution, change-feed, and search-within tools, plus memory and subscription lifecycle support. However, the nominal AbuseIPDB purpose has only three tools (check, blacklist, report) with no categories, bulk lookup, or detailed report features, and some subdomains lack updates (e.g., no subscription editing), creating notable gaps.

Resources