Researchsearch

Name: Researchsearch
Author: CloudCorpRecords

by CloudCorpRecordsversion 0.1.0i★ –iRuns on your computer

Registry nameio.github.CloudCorpRecords/researchsearch

Install

Overview

Description from the maker (original English)

Web search, page extraction, crawling, and site mapping powered by the Tavily API.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "researchsearch": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/researchsearch",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add researchsearch -- npx -y @reneturcios/researchsearch mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "researchsearch": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/researchsearch",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "researchsearch": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/researchsearch",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account CloudCorpRecords, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7243 servers in this category
Published to the registry more recently than 85% of the other 7243 servers in this category
Basic checks equal to or better than 100% of the other 7243 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Researchsearch safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 6 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated 3 days ago

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 44 days ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

researchsearch

researchsearch is a research desk for the web, powered by the Tavily API. It searches with ranked, content-bearing results (and an optional generated answer), pulls the clean text out of specific pages, crawls a site page by page under limits you set, and maps a site's structure so you can see what is there before you read it. It works from the command line or as an MCP server for agents.

A Tavily API key is required. Put it in the TAVILY_API_KEY environment variable; without it, every operation stops with an error that names the missing variable, before any request is made.

Install

export TAVILY_API_KEY="tvly-..."

npx @reneturcios/researchsearch search "composting basics"

Or run the container image:

docker run -i -e TAVILY_API_KEY="tvly-..." ghcr.io/cloudcorprecords/researchsearch

The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.

CLI

# Search; results print as JSON

researchsearch search "composting basics" researchsearch search "rate decision" --topic news --days 3 --max-results 5 --answer

Extract the clean content of one or more pages

researchsearch extract https://example.com/article researchsearch extract https://example.com/a https://example.com/b --depth advanced

Crawl a site from a starting page

researchsearch crawl https://example.com --max-depth 2 --limit 25 researchsearch crawl https://example.com --instructions "Focus on the guides"

Map a site's structure (URLs only, no page content)

researchsearch map https://example.com --max-depth 1 --limit 50

researchsearch --version

Exit codes: 0 on success, 1 when an operation fails (a missing TAVILY_API_KEY, an HTTP error from the service, an unreachable host), 2 for usage errors.

MCP server

One bin serves both faces. The mcp subcommand starts a stdio MCP server:

npx -y @reneturcios/researchsearch mcp

MCP client configuration:

"mcpServers": { "researchsearch": { "command": "npx", "args": ["-y", "@reneturcios/researchsearch", "mcp"], "env": { "TAVILY_API_KEY": "tvly-..." } } } }

Tools

Tool	Input	What it returns
`tavily-search`	`query` (string, required), `search_depth`, `topic`, `days`, `max_results`, `include_answer`, `include_raw_content`, `include_domains`, `exclude_domains` (all optional)	Ranked results with content excerpts and scores, plus a generated answer and raw page content when requested.
`tavily-extract`	`urls` (string array, required), `extract_depth`, `include_images`, `query` (optional)	The clean extracted content of each page, with failures reported separately.
`tavily-crawl`	`url` (string, required), `max_depth`, `max_breadth`, `limit`, `instructions`, `extract_depth` (optional)	The pages visited from the starting URL, each with its extracted content.
`tavily-map`	`url` (string, required), `max_depth`, `max_breadth`, `limit`, `instructions` (optional)	The list of URLs reachable from the starting page, without page content.

Each tool is one call to the matching Tavily API endpoint. Only the parameters you set are sent — unset optionals are omitted so the service applies its own defaults — and each response is the service's JSON, passed back unchanged.

Development

npm install

npm run build # tsc -> dist/ npm test # node test runner over test/*.test.ts, no network (fake fetch fixtures) npm run dev # run the CLI from source via tsx

License

MIT — see LICENSE.

Researchsearch

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

researchsearch

Install

CLI

Extract the clean content of one or more pages

Crawl a site from a starting page

Map a site's structure (URLs only, no page content)

MCP server

Tools

Development

License