PrismSearch

PrismSearch

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A multi-engine web search MCP (Model Context Protocol) server that aggregates search results from multiple search engines.

Like a prism splits light into a spectrum, PrismSearch disperses your search queries across multiple engines for multi-perspective results.

Why: web search for your AI agent, no search account required

The built-in web search of AI coding agents such as Claude Code and DeepSeek Harness usually depends on an official account or a separately configured search API key. Use a third-party model, go through your own gateway, or simply skip the search account, and the built-in search is often unavailable — the agent ends up coding "closed-book".

PrismSearch adds that capability back with one command:

• No account, no API key out of the box: the default engines (Bing, Baidu, …) scrape public result pages, so there is nothing to sign up for. Enable browser fetching (fetcher.browser.enabled: true, requires Playwright) and Google works without a key too. Brave / Google API keys are picked up automatically when present for extra reliability
• Any model, any client: plain MCP — works with Claude Code, DeepSeek Harness, Cursor, VS Code, Cline and any other MCP-capable client
• More than search: fetch_page reads web pages and PDFs (Markdown output, paginated for long documents), wechat_search searches WeChat Official Account articles — the "found it, now read it" half
• Works behind restrictive networks: Chinese sources (Baidu, Sogou, 360, WeChat) work out of the box; when an engine is blocked or rate-limited the request falls back to the next one automatically
• Clean results: sponsored results injected by search engines are removed — see "Ad filtering" below

# Claude Code

claude mcp add prismsearch -- npx -y prismsearch

[!WARNING]

Scraping engines fetch results from public web pages. You are responsible for complying with each search engine's and target site's terms of service, robots policies and local laws, and for keeping request rates reasonable.

The learning/research recommendation is not an additional restriction on the Apache-2.0 license. This project is not affiliated with any search engine company. See the full Disclaimer at the end.

Features

• 9 Search Sources: Google, Bing, Baidu, Brave, DuckDuckGo, Yandex, Sogou, 360 Search, plus WeChat Official Account articles — with an extensible engine plugin system
• 5 MCP Tools: web_search, image_search, fetch_page, wechat_search, list_engines
• Dual Transport: stdio (local) and Streamable HTTP (remote) MCP transport
• Smart Engine Selection: Auto-selects the best engine based on availability, latency, success rate, and language matching, with cross-engine fallback
• Google Triple Strategy: Custom Search API → browser rendering → plain HTTP, with automatic fallback and sticky success memory
• Ad Filtering: Baidu promotions, Bing / Google / DuckDuckGo sponsored results and 360 / Sogou paid slots are dropped and don't eat into the requested count; anything that slips through is filtered again by its landing URL (paid-click tracking parameters)
• Web Page Fetching: Fetch and extract content from URLs in HTML, plain text, or Markdown; optional Playwright rendering for JS-heavy pages
• Image Search: Multi-engine image search with size/type filters and optional base64 thumbnails
• Caching: Configurable TTL and LRU eviction with pluggable backends — cache.backend: sqlite | memory | redis (SQLite by default)
• Security: SSRF protection, rate limiting, domain whitelist/blacklist, optional Bearer auth for remote mode
• Hot Reload: Configuration file watching with automatic reload
• Flexible Config: YAML/JSON/TOML configuration with environment variable overrides

Example

A single web_search call returns structured, deduplicated results:

{

"results": [ { "title": "Model Context Protocol - Introduction", "url": "https://modelcontextprotocol.io/introduction", "snippet": "The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools.", "source": "brave", "position": 1 } ], "totalResults": 10, "engine": "brave", "searchTime": 842, "cached": false, "page": 1, "hasMore": true }

Every item in results[] always has title, url, snippet, source (the engine) and position, and may have timestamp; with mode=aggregate items also carry sources and the response carries engines. When the engine ignored some parameters the response carries warnings. The same JSON is returned both as structuredContent and as text in content.

Architecture

flowchart LR

Client["MCP client Claude Code / Cursor / …"]

subgraph Transport["Transport src/server"] Stdio["stdio"] Http["Streamable HTTP auth · Host/Origin check · rate limit"] end

subgraph Tools["Tools src/tools"] WS["web_search"] IS["image_search"] WX["wechat_search"] FP["fetch_page"] LE["list_engines"] end

subgraph Search["Search orchestration"] Sel["Engine selection / circuit breaker engine-selector"] Chain["Fallback chain · aggregate RRF dedup · ad filter"] end

Engines["Engine adapters src/engines Google · Bing · Brave · Baidu · DDG Yandex · Sogou · 360 · Sogou WeChat"] Cache[("Cache src/cache sqlite / memory / redis")]

subgraph Fetch["Fetching src/fetcher"] SSRF["SSRF guard src/security/ssrf-guard"] HF["HTTP fetcher"] BF["Browser fetcher Playwright"] WK["Remote workers ts-worker / py-worker"] EX["Content extraction Readability / PDF"] end

Client --> Stdio & Http Stdio & Http --> Tools WS & IS --> Sel --> Chain --> Engines WX --> Engines LE -. status .-> Sel WS & IS & WX & FP -. read/write .-> Cache FP --> SSRF --> HF & BF & WK HF & BF & WK --> EX

In stdio mode there is a single client, so rate limiting happens at the tool layer; in HTTP mode the transport rate-limits per client. Whether fetch_page is delegated to a worker is controlled by workers.useFor; when no worker is available it falls back to the local fetchers, and the final URL returned by a worker is SSRF-checked again.

Requirements

• Node.js ≥ 22.19
• Native module better-sqlite3 ships prebuilt binaries for mainstream platforms (Windows/macOS/Linux, x64/arm64); if prebuilds are unavailable on your platform, a C++ build toolchain is required
• Optional: Playwright for browser rendering. It is an optionalDependency — installed by default (browsers download on install); use npm install --omit=optional for a minimal install. To add it later: npm install playwright && npx playwright install chromium

Quick Start

Installation

npm install prismsearch

Usage with Claude Code

claude mcp add prismsearch -- npx -y prismsearch

Or add to your MCP settings:

{

"mcpServers": { "prismsearch": { "command": "npx", "args": ["-y", "prismsearch"], "env": { "BRAVE_API_KEY": "optional" } } } }

Other clients

On Windows, if the client cannot find npx, set command to "cmd" and args to ["/c", "npx", "-y", "prismsearch"].

Use as an Agent Skill

skills/prismsearch/SKILL.md is an Agent Skill that teaches the agent when to use each tool: search first and then read the source pages, use timeRange / aggregate mode, fall back to browser rendering, page through long documents, and handle engine failures. The MCP server above still has to be connected; the skill only adds usage guidance.

To install it for Claude Code, copy the folder into your skills directory:

# All projects

cp -r skills/prismsearch ~/.claude/skills/

Current project only

cp -r skills/prismsearch .claude/skills/

Other agents that support the Agent Skills format can load the same folder.

Use in DeepSeek Harness

dsh-plugin-prismsearch is a DeepSeek Harness plugin that installs both the MCP server and the skill in one step. In the DSH Web GUI, open Plugins → Add plugin and enter:

dsh-plugin-prismsearch

The plugin starts a pinned prismsearch version through npx, so Node.js >=22.19.0 must be on PATH. The first start downloads the package and can take a few seconds. Tools appear as mcp__prismsearch__web_search and so on. If BRAVE_API_KEY, GOOGLE_API_KEY or GOOGLE_CSE_ID are set where DSH starts, they are forwarded to the server. If you have already added an MCP entry with serverName: prismsearch by hand, remove it or rename it first, otherwise the two entries conflict. See the plugin README for details.

Engine capabilities

Parameter support per engine (web search)

How each web_search parameter is translated for each engine. "—" means the engine has no equivalent; the parameter is accepted but ignored, and the response's warnings lists which parameters were dropped. list_engines also declares per-engine suppo