Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add whw23/searxng_http_mcp --skill web-search-via-searxnggit clone --depth 1 https://github.com/whw23/searxng_http_mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/whw23/searxng_http_mcp/web-search-via-searxng)<a href="https://agentmods.dev/skills/whw23/searxng_http_mcp/web-search-via-searxng"><img src="https://agentmods.dev/badge/skills/whw23/searxng_http_mcp/web-search-via-searxng/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/whw23/searxng_http_mcp/web-search-via-searxng"><img src="https://agentmods.dev/badge/skills/whw23/searxng_http_mcp/web-search-via-searxng.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.01095 |
| Opus 5.5 | $0.00020 | $0.00438 |
| Sonnet 5.5 | $0.00010 | $0.00219 |
| Haiku 4.5 | $0.00005 | $0.00110 |
Grade A, and why
web-search-via-searxng scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SearXNG Web Search
Use the configured SearXNG MCP server to search the web.
When to Use
- Answering questions that need up-to-date information
- Looking up documentation or API references
- Researching technical topics
- Finding news or current events
- Searching for images, videos, academic papers, code, packages
How to Search
Prefer delegating to the web-searcher agent via the Agent tool. The agent handles
multi-language parallel search, source credibility verification, cross-validation,
iterative deepening, and structured summarization — returning a clean result without
polluting your context window with raw JSON. Only call the MCP search tools directly when:
- The
web-searcheragent is unavailable (e.g., no subagent support) - You need a single quick lookup where spawning an agent is overkill
MCP Tools Reference
When searching directly (without the agent), use these tools:
search
Main search tool. Parameters:
query(required): Search termscategories: Comma-separated category names (e.g., 'general,news,science'). Prefer this overengines— categories leverage multiple engines automaticallylanguage: Language code (e.g., zh, en, ja). Filters results to the specified languagetime_range: day, week, month, yearsafesearch: 0 (off), 1 (moderate), 2 (strict)pageno: Starting page number (default 1)pages: Number of pages to fetch in parallel, 1-5 (default 1). Use 2-3 for comprehensive researchmax_results: Maximum results to return (default 10, max 100)format:compact(default, title/url/content only) orfull(includes engines, score, dates)engines: Comma-separated engine names (e.g., google,arxiv,wikipedia). Only use when you need a specific source
autocomplete
Get search query suggestions. Use before searching to discover relevant terms. Best results come from 1-2 meaningful keywords (e.g., "python async"). Single characters return overly broad suggestions; full sentences return none. Makes an external API call to the configured backend (e.g., Bing, Google).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 95 lines · 50 tokens per session scan A 93348731a6a5
web-search-via-searxng is a skill published in the GitHub repository whw23/searxng_http_mcp (12 stars, last pushed 8d ago), licensed MIT. It adds 50 tokens to every session and 1,095 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
web-search-via-searxng compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| web-search-via-searxngwhw23/searxng_http_mcp | Skill | 12 | 8d ago | MIT | A | 50 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |