Where does data (embeddings, logs) live?

The project creates `data/` directories for data storage and `logs/` for log files (auto-created). FAISS vector stores and document chunks are managed locally.

What API keys are needed?

API keys for Exa and FireCrawl are mandatory. An OpenAI API key or Ollama local installation is optional depending on LLM choice.

What credentials does it need?

It reads `OLLAMA_BASE_URL` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

Search Engine With RAG And MCP Server — Tools & Setup

What is the Search Engine With RAG And MCP Server?

MCP Server supported search engine

What it actually does

A powerful search engine that combines LangChain, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and Ollama to create an agentic AI system capable of searching the web, retrieving information, and providing relevant answers.

Web search capabilities using the Exa API
Web content retrieval using FireCrawl
RAG (Retrieval-Augmented Generation) for more relevant information extraction
MCP (Model Context Protocol) server for standardized tool invocation
Support for both local LLMs via Ollama and cloud-based LLMs via OpenAI
Flexible architecture supporting direct search, agent-based search, or server mode

Configuration

Python 3.13+ - Poetry (optional, for development) - API keys for Exa and FireCrawl - (Optional) Ollama installed locally - (Optional) OpenAI API key

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Configuration

Python 3.13+ - Poetry (optional, for development) - API keys for Exa and FireCrawl - (Optional) Ollama installed locally - (Optional) OpenAI API key

Variable	Description	Required
OLLAMA_BASE_URL	Endpoint or connection string the server talks to.	Yes

Example prompts to try

“Use Search Engine With RAG And MCP to Prerequisites.”
“Use Search Engine With RAG And MCP to Installation.”
“Use Search Engine With RAG And MCP to Usage.”

Frequently asked questions

Python 3.13+ is required. Dependencies include LangChain, MCP libraries, embeddings, FAISS, and API clients for Exa and FireCrawl. Optional: Ollama for local LLM, OpenAI for cloud LLM.

Search Engine With RAG And MCP Server

What is the Search Engine With RAG And MCP Server?

What it actually does

Configuration

More MCP options

Configuration

Example prompts to try

Frequently asked questions

Alternatives to the Search Engine With RAG And MCP Server

Fetch

Firecrawl

Puppeteer

Browser MCP

Playwright

Exa

Search Engine With RAG And MCP Server

What is the Search Engine With RAG And MCP Server?

What it actually does

Configuration

More MCP options

Configuration

Example prompts to try

Frequently asked questions

What runtime and dependencies are required?

Where does data (embeddings, logs) live?

What API keys are needed?

What credentials does it need?

Alternatives to the Search Engine With RAG And MCP Server

Fetch

Firecrawl

Puppeteer

Browser MCP

Playwright

Exa