Grounder
Web grounding for local & cloud LLMs: search, fetch, token-capped evidence packs, and research.
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).
grounder-mcpclaude mcp add grounder -e 'GROUNDER_API_KEY=<your grounder_api_key>' -- uvx grounder-mcp==0.4.1{
"mcpServers": {
"grounder": {
"command": "uvx",
"args": [
"grounder-mcp==0.4.1"
],
"env": {
"GROUNDER_API_KEY": "<your grounder_api_key>"
}
}
}
}Environment variables
GROUNDER_API_KEYrequired secret Your Grounder API key - get one free at https://grounder.dev
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Grounder MCP
Live web grounding for local and cloud LLMs, as four MCP tools. Every model is frozen at its training cutoff; Grounder gives yours the current web - ranked results, real page content, and a cited evidence pack sized to your context window.
A thin stdio client for the hosted service at https://grounder.dev - no browser, no scraper, nothing heavy runs locally. It runs with no signup on a shared demo key; add your own free key (1,500 pages/month, no card) at grounder.dev for real use.
Install
uvx grounder-mcp # or: pip install grounder-mcpConfigure
Claude Desktop, Cursor, LM Studio, Continue.dev, or any MCP client. The key is optional - omit it to try Grounder on the shared demo key, or add your own free key from grounder.dev:
{
"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 people-also-ask, related searches, and the knowledge graph. The top snippet often already holds the answer. |
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, ranked into a token-capped, cited evidence pack. Optional grounded answer. |
research | Investigates an open question with no ready-made answer: it plans, reads primary sources, notices what is missing, goes back for it, and reasons to a grounded conclusion. |
Why use it
- It fits a small context window. Results come back token-capped, so they slot into an 8-32k local model instead of overflowing it. A few raw pages can be 20,000+ tokens (we measured 22,759 for one query) - enough to make a small model return nothing. You get the relevant passages, not whole pages.
- The live page, not a cached copy.
fetchreads the actual current page; any caching is short, timestamped, and force-refreshable. - Flat monthly price, billed in pages. You only pay for pages actually delivered. No per-call metering.
- No query content stored. Ever.
Pricing
Free: 1,500 pages/month, no card. Starter $9/mo, Pro $19/mo. Full table at https://grounder.dev/pricing.
Frequently asked questions
What is Grounder?
Web grounding for local & cloud LLMs: search, fetch, token-capped evidence packs, and research.
How do I install Grounder?
It runs on your machine. In Claude Code: claude mcp add grounder -e 'GROUNDER_API_KEY=<your grounder_api_key>' -- uvx grounder-mcp==0.4.1. For other clients, paste the JSON configuration from this page into their MCP settings.
Does Grounder need an API key?
Yes. It expects GROUNDER_API_KEY, which you set in its configuration.
Is Grounder open source?
Yes. Its code is on GitHub under the MIT license.
Who maintains Grounder?
It is published by rozetyp. 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.