google_searchLABSCO SUMMARY
Ranked evidence rather than a page of results, at a cost you can predict per call.
The search tool scores and classifies what it returns and everything comes back as markdown rather than HTML, which is the difference between an agent reading three good sources and an agent burning its context on navigation chrome. research_topic collapses the whole loop — search, rank, dedupe, extract, synthesise — into one call, and the pricing follows the same logic: one credit per search, extraction free.
What it is
A web-research server, published by its author as Nimrod. Four tools: quality-scored Google search, single-page extraction to markdown, up to five pages at once, and a full research pass in one call.
What you get
- google_search — organic Google results with quality scores, authority ratings and source-type classification, with date, site and language control
- extract_webpage_content — any URL turned into clean markdown with the boilerplate stripped
- extract_multiple_webpages — up to five URLs fetched concurrently
- research_topic — search, rank, dedupe, extract and synthesise, returned from a single call
- A desktop build that runs extraction on your own machine, bundled with six research skills and a deep-research agent
- Listed in the MCP Registry as ai.orchis/nimrod, so registry-aware clients can install it without a config file
Requirements
An account with the service; new accounts start with a 50-credit trial and no card. The hosted endpoint is https://nimrod.orchis.ai/mcp — add it as a custom connector and sign in, or pass an Authorization: Bearer key. Desktop builds exist for Windows, macOS and Linux; the macOS build is not Apple-signed, so it needs one xattr -d com.apple.quarantine before it will run. Search costs 1 credit and research_topic costs 1 credit plus one per focus area; extraction is free on every plan.
Setup effort
Add the hosted endpoint, then sign in — paste it into your client, then approve the OAuth sign-in
USE CASES
Researching a question that needs more than one source
One call searches, ranks, removes duplicates, reads the pages and returns a synthesis, so a research question costs a turn rather than a session.
Reading a page without the navigation and the ads
Hand it a URL and get markdown back with the boilerplate stripped — short enough for the model to actually read.
Working out which sources are worth trusting
Results arrive with quality scores, authority ratings and a source type, so the choice of what to read is made before anything is fetched.
Comparing several pages at once
Search, then pull up to five of the results concurrently and compare them in one turn.
4 tools
Listed in project docs. Your client may show a different list.
extract_webpage_contentextract_multiple_webpagesresearch_topicBEFORE YOU INSTALL
What to know first
Tools you get
4 tools named in the project's documentation.
INSTALLATION
Connect your client
Server setup
https://nimrod.orchis.ai/mcpAdd this hosted endpoint to your MCP client using the credentials listed under Requirements.
MCP Clients
Claude Code — remote
claude mcp add nimrod --transport http https://nimrod.orchis.ai/mcp --header "Authorization: Bearer <YOUR_KEY>"Claude Desktop — Windows
Download nimrod.mcpb from the latest release:
https://github.com/mixelpixx/Nimrod/releases/latestDouble-click nimrod.mcpb to open it in Claude Desktop, then paste your Nimrod key
Claude Code — macOS
Download nimrod-desktop-macos (universal: Apple Silicon + Intel) from the latest release:
https://github.com/mixelpixx/Nimrod/releases/latestchmod +x nimrod-desktop-macos
xattr -d com.apple.quarantine nimrod-desktop-macos
./nimrod-desktop-macos setup
claude mcp add nimrod -- <YOUR_PATH_TO_NIMROD_DESKTOP_MACOS>Claude Code — Linux
Download nimrod-desktop-linux from the latest release:
https://github.com/mixelpixx/Nimrod/releases/latestchmod +x nimrod-desktop-linux
./nimrod-desktop-linux setup
claude mcp add nimrod -- <YOUR_PATH_TO_NIMROD_DESKTOP_LINUX>