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Grounder MCP

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Grounder MCP thin client - live web search, fetch, deep_search evidence packs, and agentic research for local & cloud LLMs. Backed by grounder.dev.

Grounder MCP

Live web grounding for local and cloud LLMs, as four MCP tools. Every model is frozen at itstraining cutoff; Grounder gives yours the current web - ranked results, real page content, and acited evidence pack sized to your context window.

This is a thin stdio client for the hosted service at grounder.dev - nobrowser, no scraper, nothing heavy runs locally. Get a key (free, no card) at grounder.dev.

Install

uvx grounder-mcp          # or: pip install grounder-mcp

Configure

Claude Desktop, Cursor, LM Studio, Continue.dev, or any MCP client:

{
  "mcpServers": {
    "grounder": {
      "command": "uvx",
      "args": ["grounder-mcp"],
      "env": { "GROUNDER_API_KEY": "gnd_live_your_key" }
    }
  }
}

The four tools

Tool What it does
web_search Google organic results plus the surfaces around them - people-also-ask, related searches, knowledge graph. The top snippet often already holds the answer, so the model can skip a fetch.
fetch One page as clean markdown, capped to your token budget, plus the final URL after redirects.
deep_search One search, read across the pages it surfaces, chunked and ranked into a token-capped, cited evidence pack. Optional grounded answer, written only from what it read.
research Investigates an open question with no ready-made answer - the kind you'd hand an analyst: it plans, reads primary sources, notices what is still missing, goes back for it, and answers only from the pages it actually read.

Why use it

  • It fits a small context window. Results come back token-capped, so they slot into an 8-32klocal model instead of overflowing it. A few raw web pages can be 20,000+ tokens - we measured22,759 for one query - which is enough to make a small model return nothing at all. deep_searchand research hand back the relevant passages, not whole pages.
  • The live page, not a cached copy. fetch reads the actual current page on request. Any cachingis short, timestamped, and force-refreshable - it never turns into an opaque stale index.
  • Flat monthly price, billed in pages. One page is one search, one fetch, or one page adeep_search reads, and you only pay for pages actually delivered - an empty search or anunreadable page is free. No per-call metering.
  • No query content stored. Ever.
  • Nothing heavy to run. The client just forwards tool calls to the hosted API, so it installs inseconds with no browser or scraping stack on your machine.

Pricing

Free: 1,500 pages/month, email only, no card. Starter $9/mo and Pro $19/mo add higher page budgets,protected-page access, and more research runs. Full table atgrounder.dev/pricing.

Links

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