Combined MCP Server

A production-grade MCP (Model Context Protocol) server combining Redshift query capabilities and Knowledgebase vector store features.

Features

Redshift Tools

run_query - Execute SQL with IAM authentication via get_cluster_credentials
list_schemas - List database schemas
list_tables - List tables in a schema
describe_table - Get table structure

Large results (>100 rows) are automatically stored in S3 with 20 sample rows returned.

Knowledgebase Tools

build_vectorstore - Build vector store from S3 markdown files
query_vectorstore - Hybrid search (semantic + keyword) with RRF reranking
get_vectorstore_status - Check build status and cache stats

Quick Start

Local Development

Install uv (if not already installed):

curl -LsSf https://astral.sh/uv/install.sh | sh
# Or on Windows: powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Start infrastructure:

docker-compose up -d postgres localstack

Install dependencies:
```
uv pip install -e ".[dev]"
```

Configure environment:

cp .env.example .env.local
# Edit .env.local with your settings

Run the server:

# With MCP Inspector
mcp dev src/combined_mcp_server/main.py

# Or directly
python -m combined_mcp_server.main

ECS Deployment

# Build container
docker build -t combined-mcp-server .

# Run with health checks
docker run -p 8080:8080 --env-file .env combined-mcp-server

Health endpoints:

GET /health - Liveness probe
GET /ready - Readiness probe
GET /status - Detailed status

Configuration

See .env.example for all configuration options. Key settings:

Variable	Description
`REDSHIFT_CLUSTER_ID`	Redshift cluster identifier
`POSTGRES_SECRET_NAME`	Secrets Manager secret for pgvector DB
`KNOWLEDGEBASE_S3_BUCKET`	S3 bucket with markdown files
`BEDROCK_EMBEDDING_MODEL`	Titan embedding model ID

Architecture

┌─────────────────────────────────────────────────────┐
│                  Combined MCP Server                 │
├─────────────────────┬───────────────────────────────┤
│   Redshift Tools    │     Knowledgebase Tools       │
│  ─────────────────  │  ───────────────────────────  │
│  • run_query        │  • build_vectorstore          │
│  • list_schemas     │  • query_vectorstore          │
│  • list_tables      │  • get_vectorstore_status     │
│  • describe_table   │                               │
├─────────────────────┴───────────────────────────────┤
│                    Core Services                     │
│  AWS (Secrets Manager, S3, Bedrock, Redshift)       │
│  PostgreSQL + pgvector                              │
└─────────────────────────────────────────────────────┘

Testing

# Unit tests
pytest tests/ -v

# With coverage
pytest tests/ -v --cov=combined_mcp_server

# Integration tests (requires Docker)
docker-compose up -d
pytest tests/ -v -m integration

License

MIT

mcp_servers