# deep-research-mcp

> deep-research-mcp — pinkpixel-dev-deep-research-mcp. Use this tool when you need to conduct comprehensive web research and generate high-quality markdown documents on a specific topic. It solves problems of information gathering and data structuring by leveraging Tavily's Search and Crawl APIs to collect detailed data, which is then formatted for large language models (LLMs) to create informative documents. Ideal for use cases requiring in-depth research and document creation, with inputs including topic queries and outputs including structured markdown files.

Canonical page: https://skillsregistry.net/skills/pinkpixel-dev-deep-research-mcp  
JSON: https://api.skillsregistry.net/v1/skills/pinkpixel-dev-deep-research-mcp

## Description

A Model Context Protocol (MCP) compliant server designed for comprehensive web research. It uses Tavily's Search and Crawl APIs to gather detailed information on a given topic, then structures this data in a format perfect for LLMs to create high-quality markdown documents.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** browser-automation
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/pinkpixel-dev/deep-research-mcp)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "pinkpixel-dev-deep-research-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pinkpixel-dev-deep-research-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pinkpixel-dev-deep-research-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt