gapup-mcp

web_search_multilang

Read-only

Multi-language, multi-source web search that goes beyond Anglo-centric results. Supports 15 languages (fr/de/es/it/pt/nl/ja/zh/ko/ar/ru/sv/pl/tr/en) with automatic detection. Aggregates results from Mojeek (independent search engine, multilang) and Wikipedia (native multilang API), with DDG and HN as English-language complements. Returns deduplicated results ranked by cross-engine consensus. Use when you need non-English search results, when DDG fails, or for geographically-biased queries. Phase 2 #7 of the geo/lang expansion plan. Note: Brave/Bing/Searx are blocked from DO IPs — configure AICI_RESEARCH_PROXY_URL for residential proxy.

Input Schema

TableJSON Schema

Name	Required	Description
`lang`	No	2-letter language code. If omitted, auto-detected from query characters and lexical markers.
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
`query`	Yes	Search query in any language
`country`	No	ISO-3166-1 alpha-2 country code for geographic bias (e.g. FR, DE, JP, BR). Optional.
`max_results`	No	Maximum number of results to return (default 10).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes
`status`	Yes
`results`	Yes
`sources`	Yes
`by_engine`	Yes
`lang_used`	Yes
`country_used`	No
`quality_score`	Yes
`total_unique_results`	Yes

TDQS

A4.9/5.0

Behavior5/5

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

The description discloses key behaviors beyond annotations: aggregation from Mojeek, Wikipedia, DDG, HN; deduplication; async mode with job polling; proxy configuration for blocked IPs. No contradictions with readOnlyHint and destructiveHint 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 a single focused paragraph with no wasted words. It is front-loaded with purpose, followed by key details (languages, sources, usage guidance, notes). Every sentence serves a purpose.

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?

Given the tool's complexity (multi-source, multi-language, async, geo-bias, proxy), the description covers all essential aspects. It mentions output characteristics (deduplicated, consensus-ranked) and provides necessary operational context (blocked IPs, proxy setup).

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 baseline is 3. The description adds value by explaining lang auto-detection, async behavior (returns job_id), country for geographic bias, and max_results default. However, it doesn't add significant meaning beyond the individual schema descriptions for each parameter.

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 the tool's purpose: 'Multi-language, multi-source web search that goes beyond Anglo-centric results.' It specifies the verb 'search', the resource 'web', and distinguishes itself from other search tools by emphasizing multi-language and multi-source aggregation.

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?

The description provides explicit guidance: 'Use when you need non-English search results, when DDG fails, or for geographically-biased queries.' It also mentions limitations (blocked from DO IPs) and configuration requirements, helping the agent decide when to use this tool versus alternatives.

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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TDQS

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

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