Enterprise RAG System with MCP Agents
A production retrieval-augmented generation platform that answers staff questions over a large enterprise document corpus with citations, plus MCP agents for multi-step tool use.
Project Overview
A production retrieval-augmented generation platform that answers staff questions over a large enterprise document corpus with citations, plus MCP agents for multi-step tool use.
The Problem
An enterprise knowledge base was effectively unsearchable. Staff spent hours hunting for answers that already existed somewhere in the corpus, and keyword search could not keep up with how people actually ask questions.
The Solution
A production RAG platform with hybrid retrieval and citation grounding, extended with MCP agents for multi-step tool use, served via FastAPI with caching, validation, and quality monitoring.
Use Cases
Citation-grounded answers
Responses cite their sources from the enterprise corpus.
Hybrid retrieval
Chunking plus hybrid search tuned for accurate, useful recall.
MCP tool-using agents
Agents reason over multiple steps and call tools through MCP.
Reliability layers
Caching and validation keep answers fast and trustworthy.
Production serving
API serving with quality and latency monitoring.
Scalable corpus
Indexed and searchable across a large enterprise document set.
Architecture & Flow
What I Delivered
- RAG pipeline with hybrid retrieval and citation grounding
- MCP agent layer for multi-step tool use
- Caching and validation for reliability
- FastAPI service with retrieval-quality monitoring
- Faster search across the enterprise corpus
Ready to build something useful?
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