assafelovic/gptr-mcp

Score: 26.6 Rank #8160

MCP server for enabling LLM applications to perform deep research via the MCP protocol

Overview

assafelovic/gptr-mcp is a Python MCP server licensed under MIT. MCP server for enabling LLM applications to perform deep research via the MCP protocol Topics: gpt-researcher, mcp, mcp-server, deep-research, deepresearch, websearch.

Ranked #8160 out of 25632 indexed tools.

Ecosystem

Python MIT

gpt-researchermcpmcp-serverdeep-researchdeepresearchwebsearch

Signal Breakdown

Stars 330

Freshness 4mo ago

Issue Health 22%

Contributors 3

Dependents 0

Forks 53

Description Good

License MIT

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Freshness high impact

Last commit was 129 days ago — a recent commit would boost your freshness score

Issue Health high impact

You have 14 open vs 4 closed issues — triaging stale issues improves health

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Details

Stars: 330
Forks: 53
Open Issues: 14
Closed Issues: 4
Contributors: 3
Dependents: —
Language: Python
License: MIT
Last Commit: 4mo ago

Matched Queries

"mcp server""mcp-server"

From the README

<div align="center" id="top">

# 🔍 GPT Researcher MCP Server

</div>

## Why GPT Researcher MCP?

While LLM apps can access web search tools with MCP, **GPT Researcher MCP delivers deep research results.** Standard search tools return raw results requiring manual filtering, often containing irrelevant sources and wasting context window space.

GPT Researcher autonomously explores and validates numerous sources, focusing only on relevant, trusted and up-to-date information. Though slightly slower than standard search (~30 seconds wait), it delivers:

- ✨ Higher quality information
- 📊 Optimized context usage
- 🔎 Comprehensive results
- 🧠 Better reasoning for LLMs

## 💻 Claude Desktop Demo
https://github.com/user-attachments/assets/ef97eea5-a409-42b9-8f6d-b82ab16c52a8

## 🚀 Quick Start with Claude Desktop

**Want to use this with Claude Desktop right away?** Here's the fastest path:

1. **Install dependencies:**
   ```bash
   git clone https://github.com/assafelovic/gptr-mcp.git

Read full README on GitHub →

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