Gpt Researcher
VerifiedAutonomous agent for deep factual research reports using LLMs.
What is the Gpt Researcher MCP server?
The architecture separates planning from execution: a planner creates objective research questions while parallel execution agents crawl sources, summarize findings, and track citations. Results are aggregated into comprehensive reports with optional AI-generated images and JavaScript-enabled scraping for dynamic content.
It addresses common LLM limitations such as token constraints and outdated knowledge by maintaining memory across steps and aggregating over 20 sources. Users can customize agents for domain-specific tasks and export outputs to PDF or Word formats.
Install & connect
Add this to your MCP client config. Pick your client below and copy.
{
"mcpServers": {
"gpt-researcher": {
"command": "npx",
"args": [
"-y",
"skills"
]
}
}
}Package: skills (npm)
Other ways to install
npx
npx -y skillspip
pip install -rExample prompts
Once connected, try asking your AI client:
Security & permissions
Runs locally via stdio and requires LLM API keys plus optional web search credentials. It accesses local files and external websites during scraping.
What you can do with Gpt Researcher
Market Analysis
Generate objective reports on emerging technologies by aggregating data from multiple web sources with full citations.
Academic Research
Produce long-form literature reviews or topic summaries using local documents combined with current web information.
Competitive Intelligence
Research competitors or industries while filtering for unbiased conclusions and maintaining source traceability.
How to use Gpt Researcher
- 1Install via pip or Docker as described in the official documentation.
- 2Configure LLM provider API keys in the environment.
- 3Launch the server using stdio transport for MCP integration.
- 4Submit research queries through your MCP-compatible client.
- 5Review generated reports with citations and export as needed.
Gpt Researcher: pros & cons
Pros
- +Produces long, cited reports with objective multi-source aggregation
- +Supports parallel agent execution for faster research
- +Highly customizable for domain-specific agents and any LLM
Cons
- –Requires API keys and can incur LLM usage costs
- –Web scraping may be affected by site changes or anti-bot measures
- –Setup involves multiple configuration steps for full functionality
Frequently asked questions
It works with any LLM provider through standard API integration.
User reviews
Verified reviews from the community shape this listing's rating.
Loading reviews…
Similar MCP servers
Other search & web connectors worth a look.
