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web-search

web-search

Remote
github.com/PROJECT-B-26Search1Updated 19w ago
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About web-search

web-search is a hosted MCP server for agents that combines six web search engines behind one tool. It routes queries by price and quality, caches repeats, and fails over when an engine degrades.

Key features

  1. 01Search across six engines
  2. 02Price- and quality-based routing
  3. 03Cached repeat queries
  4. 04Automatic engine failover
  5. 05Structured results with cost metadata

Use cases

  1. 01Give an agent web search through one MCP tool
  2. 02Filter search by mode, freshness, language, or domain
  3. 03Inspect the source engine and billed cost

MCP support

Exposes a `search` tool through a hosted Streamable HTTP endpoint, with an optional stdio server that forwards to the hosted API.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://api.groundroute.ai/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

GroundRoute, web search MCP server

Glama score License: MIT Python 3.12+ MCP compatible Smithery

Give your AI agent web search across 6 engines through one MCP search tool. Hosted. Routed. Cached.

Why GroundRoute

  • One tool, six engines. Serper, Brave, Exa, Tavily, Firecrawl, Perplexity, behind a single search call. Stop wiring up six APIs, six SDKs, six billing portals.
  • Never more than going direct. Gain-share pricing: you keep ~half of every cache saving, GroundRoute keeps ~half. On a miss, you just pay the engine. BYOK supported.
  • Routing, caching, failover, on by default. Each query goes to the cheapest engine that clears a quality bar. Repeats serve from cache. If an engine degrades, we fall back automatically. No agent code changes.

See it work (5 seconds)

A call to the search tool:

{
  "name": "search",
  "arguments": { "query": "what is RAGflow", "max_results": 3 }
}

The response (trimmed):

{
  "results": [
    {
      "url": "https://ragflow.io/docs/",
      "title": "Quickstart - RAGFlow",
      "snippet": "RAGFlow is an open-source RAG engine based on deep document understanding...",
      "source_engine": "serper"
    },
    {
      "url": "https://github.com/infiniflow/ragflow",
      "title": "RAGFlow is a leading open-source Retrieval-Augmented Generation engine",
      "snippet": "RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine...",
      "source_engine": "serper"
    }
  ],
  "meta": {
    "request_id": "req_abc123",
    "cache_tier": "miss",
    "degraded": false,
    "cost_usd": 0.0021
  }
}

source_engine tells you which engine answered. meta exposes the cache tier and billed cost per call.

Benchmarked, not just shipped

We ran 170 real agent queries across all 6 engines, judged by an LLM, to map cost vs. quality per query class. Full methodology and per-engine results: State of AI Search.


Install

The hosted endpoint is https://api.groundroute.ai/mcp (streamable-HTTP). Get an API key at groundroute.ai/keys.

Claude Desktop / Claude Code, add to your MCP config:

{
  "mcpServers": {
    "groundroute": {
      "type": "http",
      "url": "https://api.groundroute.ai/mcp",
      "headers": { "Authorization": "Bearer gr_YOUR_KEY" }
    }
  }
}

Cursor, ~/.cursor/mcp.json:

{ "mcpServers": { "groundroute": { "url": "https://api.groundroute.ai/mcp",
  "headers": { "Authorization": "Bearer gr_YOUR_KEY" } } } }

VS Code (native MCP / Continue), .vscode/mcp.json:

{ "servers": { "groundroute": { "type": "http", "url": "https://api.groundroute.ai/mcp",
  "headers": { "Authorization": "Bearer gr_YOUR_KEY" } } } }

Local / stdio-only clients, bridge stdio to HTTP with mcp-remote:

{ "mcpServers": { "groundroute": {
  "command": "npx",
  "args": ["-y", "mcp-remote", "https://api.groundroute.ai/mcp", "--header", "Authorization:Bearer gr_YOUR_KEY"]
} } }

Run this repo's stdio server (optional)

This repo also ships a small native stdio MCP server (server.py) that forwards to the hosted API, useful for stdio-only clients or containerized runs.

pip install -r requirements.txt
GROUNDROUTE_API_KEY=gr_YOUR_KEY python server.py

Or with Docker:

docker build -t groundroute-mcp .
docker run -i -e GROUNDROUTE_API_KEY=gr_YOUR_KEY groundroute-mcp

Introspection (tool discovery) works with no key; running a search requires GROUNDROUTE_API_KEY (get one at https://groundroute.ai/keys).

The search tool

ParamTypeNotes
querystringrequired
modeenumauto (default), web, news, academic, answer, page
max_resultsintegerdefault 10, max 50
freshnessenumfresh, semi, static; omit to auto-detect
domainsstring[]include-only domain filter, e.g. ["arxiv.org"]
langstringISO 639-1 language code, e.g. en
countrystringISO 3166-1 alpha-2 country code, e.g. us

Returns a structured result: ranked results (url / title / snippet / content / source_engine / published_at), an optional synthesized answer with citations (answer mode), and meta (request_id / cache_tier / degraded / cost_usd). Routed, cached, and reliable.

How it works

One endpoint in front of many search engines, with price-led routing, caching, failover, and usage governance. See the docs and the State of AI Search benchmark (170 real agent queries across all 6 engines).

Links

registry-manifest.json in this repo is the listing manifest for MCP registries.

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