Searchpin — Free Web Search for AI Agents

Self-hosted web search for AI agents — zero API keys, zero cost. In 2026, the center of gravity in AI development is shifting from "chatting" to "autonomous task execution" — locally deployed, long-running agents are becoming the norm. When an agent runs 24/7, every web search must not be interrupted by API quotas or billing. Searchpin was designed for this from day one: zero external dependencies, zero usage limits. Agents can search, fetch, and verify without restriction, and developers never worry about cost.

🇨🇳 Optimized for Chinese Network Environments

Defaults toBaidu, Sogou, Bing CN, and Bing Intl— four search engines queried in parallel. Works natively within China's network, no proxy or VPN needed. Most overseas alternatives rely on Google, DuckDuckGo, or Brave, which are largely inaccessible inside China.

🧠 Semantic Re-ranking — a Differentiator Few Offer

Results from all four engines are not simply concatenated. They are merged and re-ranked by an embedding model based on semantic similarity to the query. What your AI receives is a curated list of high-quality results, not a pile of noisy links. Among free MCP search servers, very few offer this capability.

No account registration, no API key application, no usage limits. No dependency on any commercial API — no risk of sudden paywalls or quota restrictions. The entire pipeline runs on your own machine.

Built-in SSR content extraction can parse pages rendered by Next.js, Nuxt, and similar frameworks, and extract JSON-LD structured data and microdata. Plain HTML scraping gets nothing from these sites.

🛡️ Pollution Detection + Cross-Verification

Automatically detects and flags results unrelated to your query. Four independent search engines provide cross-verifiable results, enabling your LLM to corroborate information across sources for more credible answers.

Every design decision was made with real-world usage in mind:

- Token-conscious— Search results return only titles, URLs, and snippets. Structured extraction data is compact and truncated. Your LLM decides which pages are worth fetching in full, without wasting context window.
- Fast response— Four engines queried asynchronously in parallel. Total time depends on the slowest engine, not the sum of all four. A typical search completes in 1–2 seconds.
- Memory-friendly— The embedding model (~118MB) is downloaded once through hf-mirror.com (HuggingFace mirror for China), then reused from local cache.

pip install searchpin && searchpin-setup

On first run, the embedding model (~118MB) is downloaded once via hf-mirror.com (HuggingFace mirror for China). That is the only one-time setup.

Claude Desktop / Cursor / any MCP client

{ "mcpServers": { "Searchpin": { "command": "searchpin-server", "args": [] } } }

{ "servers": { "Searchpin": { "command": "searchpin-server", "args": [] } } }

docker run -i --rm ghcr.io/telly6/searchpin:latest

from searchpin import SearchEngine engine = SearchEngine() results = engine.search("Python 3.13 新特性") page = engine.fetch("https://docs.python.org/3/whatsnew/3.13.html") engine.close()

Search global news using natural language. Webz.io News Search API returns the most relevant articles and content, with filters for source, country, language, date, sentiment, and category.

An MCP server providing semantic search capabilities for APLCart data.

MCP server for Christian scholarship and research — scripture, Greek/Hebrew word data, cross-references, patristic texts, and semantic search,

Access and search EPUB ebook collections using semantic vector search.

local-first semantic search in Lojban dictionaries

Search 419,000+ space regulatory filings from the FCC, ITU, UNOOSA, and FAA-AST — semantic search, entity dossiers, spectrum holdings, launch licenses, and alerts.

The MCP server provides end-to-end workflows for SEC filings and earnings call transcripts—including ticker resolution, document retrieval, OCR, embedding, on-disk resource discovery, and semantic search—exposed via MCP and powered by the same olmOCR and embedding backends as the vLLM backends.

MCP server that enables AI assistants to search Reddit conversations, explore subreddits, and access trending topics.

Provides semantic search across local files by creating vector embeddings from watched directories.

Embeddings, vector search, document storage, and full-text search with the open-source AI application database

Semantic search through Dickens' classic tale. Find passages by meaning, theme, or concept - not just keywords.