ai.groundroute/web-search

Official registry Search and web

Web search for AI agents — one tool across 6 engines, routed to the cheapest + cached.

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code
claude mcp add --transport http web-search 'https://api.groundroute.ai/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "web-search": {
            "type": "http",
            "url": "https://api.groundroute.ai/mcp"
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Why GroundRoute
  2. See it work (5 seconds)
  3. Benchmarked, not just shipped
  4. Install
  5. Run this repo's stdio server (optional)
  6. The search tool
  7. How it works
  8. Links

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).

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

Frequently asked questions

What is ai.groundroute/web-search?

Web search for AI agents — one tool across 6 engines, routed to the cheapest + cached.

How do I install ai.groundroute/web-search?

It runs as a remote server. In Claude Code: claude mcp add --transport http web-search 'https://api.groundroute.ai/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does ai.groundroute/web-search need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is ai.groundroute/web-search open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains ai.groundroute/web-search?

It is published by PROJECT-B-26. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.