About Researcher Agent
Researcher Agent is an MCP server published by lgesuellip in the Search category: an application built on the Model Context Protocol (MCP) that transforms any website into highly relevant content based on your queries. The app seamlessly integrates with platforms like X, Slack, and among others.
The repository has 62 stars and 8 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/lgesuellip/researcher_agentThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Ask AI
Ask AI about Researcher Agent
Powered by Claude · Grounded in docs
Security checks
Static checks derived from the repository yesterday. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- ✓License declaredUsable under a stated license.
- !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
- ✓Dependencies pinnedA lockfile pins dependency versions.
- ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
1 check has not been run yet.
README
An application built on the Model Context Protocol (MCP) that transforms any website into highly relevant content based on your queries. The app seamlessly integrates with platforms like X, Slack, and others through Arcade.
Perfect For
- LLM-Ready File Creation: Generate .txt files optimized for use with large language models.
- Documentation Indexing: Organize and structure documentation effortlessly.
- Research Automation: Save time by automating repetitive research tasks.
Tech Stack
- LangGraph as the MCP Client
- Firecrawll for web research (site mapping, intelligent selection, and scraping)
- Arcade for seamless platform integration (X, Slack, etc.)
- Tracing powered by LangChainAI LangSmith
- Utilizes OpenAI's structured outputs, async processing, exponential backoff, and Pydantic for reliability
Architecture Diagram

README fetched from the repository yesterday. The original is authoritative.