7.8
/ 10
1 evaluations
1.8k Downloads
Overview
Provide the assistant with web search capabilities via a user-controlled, self-hosted SearXNG instance that returns structured JSON search results.
Key Advantages
1.Privacy-preserving search since all queries go through a self-hosted SearXNG instance with no third-party API keys or tracking.
2.Meta-search across 70+ engines (Google, DuckDuckGo, Brave, Startpage, etc.) to increase coverage and reduce single-engine bias.
3.Rich filtering via categories (general, images, news, videos, IT, science) and language/region parameters.
4.Structured JSON output (title, url, content snippet, engines, score, category) that is easy for tools and agents to consume programmatically.
5.Docker-based deployment instructions provided, including example settings.yml with JSON API enabled, lowering setup friction for technical users.
Use Cases
- General-purpose web search for users who do not want to rely on proprietary search APIs or share queries with third-party providers.
- Research workflows where the assistant needs to aggregate results from multiple engines (e.g., tech documentation, academic/science queries).
- Privacy- and compliance-sensitive environments (self-hosted, on-premise) where external API usage is restricted or monitored.
- Developer and DevOps use: querying IT/tech documentation, troubleshooting guides, and manuals via the IT category.
- Automation scripts or command-line workflows that call SearXNG’s JSON API and then feed results into the assistant for summarization or analysis.
Evaluation Scores
7.8
/ 10
Reliability
8.0
Functionality
8.8
Usability
7.0
Safety
7.8
Performance
8.2
Compatibility
6.5
Based on 1 evaluation · Latest: 3/19/2026
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7.8/103/19/2026▼
OS: win32-x64LLM: arcee-ai/trinity-large-preview
**Quick judgment**: This skill is a solid, privacy-friendly way to give the assistant web search via a self-hosted SearXNG instance. It’s powerful and flexible but assumes the user can run and maintain SearXNG (typically via Docker), so it is best suited to technically comfortable users or organizations.
**What it does well**
- Uses a self-hosted SearXNG instance as a meta-search engine, aggregating results from 70+ sources.
- Supports categories (general, images, news, videos, IT, science), pagination, and language/region filters.
- Returns structured JSON (title, URL, snippet, engines, score, category), which is ideal for tool-driven agents.
- Prioritizes privacy by avoiding third-party API keys and central tracking.
**Key risks and limitations**
- **Setup burden**: Requires SearXNG to be running and correctly configured (Docker, `settings.yml` with JSON format, `SEARXNG_URL`); non-technical users may struggle.
- **Content risk**: Like any web search, results can include outdated, biased, or unsafe content; the assistant must not treat results as inherently trustworthy and should apply normal critical filtering.
- **Configuration mistakes**: Misconfiguring SearXNG (e.g., exposing it publicly without auth, logging queries, or leaving defaults like `secret_key` unchanged) can weaken privacy or security.
- **Engine rate limits**: Some upstream search engines may rate-limit or fail; users may see incomplete or inconsistent results depending on SearXNG’s configuration and traffic.
**Recommended scenarios**
- You already run (or are willing to run) SearXNG locally or on a server and want the assistant to have web access without using commercial search APIs.
- You work in a privacy- or compliance-sensitive context and need all search traffic to stay within your own infrastructure.
- You want meta-search capabilities (multiple engines, categories, language filters) exposed cleanly to an AI agent for research or automation workflows.
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