amazon-bedrock-knowledge-base-mcp 0.1.1
Standalone Model Context Protocol (MCP) server for Amazon Bedrock Knowledge Base Retrieval
License: Apache-2.0
Requires Python: >=3.10

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<h1>Amazon Bedrock Knowledge Base MCP Server</h1>

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<p>A powerful MCP server for querying Amazon Bedrock Knowledge Bases. Retrieve semantically relevant passages with metadata filtering, reranking, and multi-transport support.</p>

<div class="toc">
  <a href="#features">Features</a> •
  <a href="#architecture">Architecture</a> •
  <a href="#quick-start">Quick Start</a> •
  <a href="#available-tools">Available Tools</a> •
  <a href="#metadata-schema">Metadata Schema</a> •
  <a href="#limitations">Limitations</a> •
  <a href="#license">License</a>
</div>

</div>

---

## Features

- **Dual Transport** - STDIO for Claude Desktop, Streamable HTTP for ChatGPT
- **Smart Filtering** - Schema-driven `where` constraints + raw Bedrock filters + implicit filtering
- **Reranking** - Optional AMAZON or COHERE reranking for improved relevance
- **Auto Schema Discovery** - Automatically infer metadata schemas from retrieval results
- **OAuth Support** - Auth0 integration for secure ChatGPT connections
- **Read-Only** - Safe by design; no write operations to your knowledge bases

---

## Architecture

![Architecture](https://raw.githubusercontent.com/Zlash65/amazon-bedrock-knowledge-base-mcp/v0.1.0/assets/architecture.png)

---

## Quick Start

### Claude Desktop (STDIO)

Add to your Claude Desktop config:

| Platform | Config Location |
|----------|-----------------|
| macOS | `~/Library/Application Support/Claude/claude_desktop_config.json` |
| Windows | `%APPDATA%/Claude/claude_desktop_config.json` |

```json
{
  "mcpServers": {
    "bedrock-kb": {
      "command": "uvx",
      "args": ["amazon-bedrock-knowledge-base-mcp"],
      "env": {
        "AWS_PROFILE": "your-profile",
        "AWS_REGION": "us-west-2"
      }
    }
  }
}
```

### ChatGPT (Streamable HTTP)

```bash
AWS_PROFILE=your-profile \
AWS_REGION=us-west-2 \
MCP_TRANSPORT=streamable-http \
uvx amazon-bedrock-knowledge-base-mcp
```

Then configure ChatGPT to connect to `https://your-domain.example.com/mcp`.

> **Note:** ChatGPT requires HTTPS. Use a tunnel (ngrok, Cloudflare Tunnel) for local testing.

---

## Available Tools

### Discovery Tools

| Tool | Description |
|------|-------------|
| `ListKnowledgeBases` | List available knowledge bases and their data sources. Filters by tag. |
| `DescribeMetadataSchema` | Show the resolved metadata schema for filtering (static or auto-discovered). |

### Query Tools

| Tool | Description |
|------|-------------|
| `QueryKnowledgeBases` | Retrieve relevant passages. Content-focused, minimal output. |
| `QueryKnowledgeBasesWithMetadata` | Retrieve passages + full metadata. Ideal for exploration and filter tuning. |

### Recommended Workflow

1. **List** - Call `ListKnowledgeBases` to find available knowledge bases
2. **Explore** - Use `QueryKnowledgeBasesWithMetadata` to discover metadata keys/values
3. **Schema** - Call `DescribeMetadataSchema` to see available filter fields
4. **Query** - Use `QueryKnowledgeBases` with `where` filters for precise retrieval

---

## Environment Variables

### AWS Configuration

| Variable | Required | Default | Description |
|----------|----------|---------|-------------|
| `AWS_PROFILE` | Yes* | - | AWS profile name (recommended) |
| `AWS_REGION` | Yes* | - | AWS region (e.g., `us-west-2`) |

*Either `AWS_PROFILE` or IAM role credentials are required.

### Knowledge Base Discovery

| Variable | Default | Description |
|----------|---------|-------------|
| `KB_INCLUSION_TAG_KEY` | `mcp-multirag-kb` | Only include KBs tagged with `<key>=true` |

### Retrieval Defaults

| Variable | Default | Description |
|----------|---------|-------------|
| `BEDROCK_KB_RERANKING_ENABLED` | `false` | Enable reranking by default |
| `BEDROCK_KB_SEARCH_TYPE` | `DEFAULT` | `DEFAULT`, `HYBRID`, or `SEMANTIC` |

### Filtering

| Variable | Default | Description |
|----------|---------|-------------|
| `BEDROCK_KB_FILTER_MODE` | `explicit_then_implicit` | How to combine explicit and implicit filters |
| `BEDROCK_KB_ALLOW_RAW_FILTER` | `false` | Allow raw Bedrock RetrievalFilter passthrough |
| `BEDROCK_KB_SCHEMA_MAP_JSON` | - | Path to KB ID → schema-path mapping (JSON) |
| `BEDROCK_KB_SCHEMA_DEFAULT_PATH` | - | Default schema file path (JSON) |
| `BEDROCK_KB_IMPLICIT_FILTER_MODEL_ARN` | - | Model ARN for implicit filtering |

### HTTP Server (Streamable HTTP only)

| Variable | Default | Description |
|----------|---------|-------------|
| `MCP_TRANSPORT` | `stdio` | Transport mode: `stdio`, `sse`, or `streamable-http` |
| `MCP_HOST` | `127.0.0.1` | HTTP server bind address |
| `PORT` | `8000` | HTTP server port |
| `MCP_STATELESS` | `true` | Stateless mode (recommended for production) |
| `MCP_ALLOWED_ORIGINS` | - | Comma-separated allowed CORS origins (`*` for any) |
| `MCP_ALLOWED_HOSTS` | - | Comma-separated allowed Host headers |

### OAuth (Auth0)

| Variable | Required | Description |
|----------|----------|-------------|
| `MCP_AUTH_MODE` | No | Set to `oauth` to enable Auth0 authentication |
| `AUTH0_DOMAIN` | Yes* | Auth0 tenant domain (e.g., `tenant.us.auth0.com`) |
| `AUTH0_AUDIENCE` | Yes* | Auth0 API identifier / audience |
| `MCP_RESOURCE_URL` | Yes* | Public URL clients connect to |

*Required when `MCP_AUTH_MODE=oauth`

### Logging

| Variable | Default | Description |
|----------|---------|-------------|
| `FASTMCP_LOG_LEVEL` | `INFO` | Log level (`DEBUG`, `INFO`, `WARNING`, `ERROR`) |

---

## Documentation

| Guide | Description |
|-------|-------------|
| [STDIO Setup](docs/stdio-setup.md) | Claude Desktop and local development |
| [Streamable HTTP](docs/streamable-http.md) | HTTP server setup and configuration |
| [Server Setup](docs/server-setup.md) | Deploy to production with nginx and SSL |
| [ChatGPT Setup](docs/chatgpt-setup.md) | Complete Auth0 OAuth setup for ChatGPT |

---

## Docker

```bash
# Build the image
docker build -t amazon-bedrock-knowledge-base-mcp:local .

# Run with AWS credentials
docker run --rm \
  -v "$HOME/.aws:/home/app/.aws:ro" \
  -e AWS_PROFILE=your-profile \
  -e AWS_REGION=us-west-2 \
  amazon-bedrock-knowledge-base-mcp:local

# Run as HTTP server
docker run --rm \
  -p 8000:8000 \
  -v "$HOME/.aws:/home/app/.aws:ro" \
  -e AWS_PROFILE=your-profile \
  -e AWS_REGION=us-west-2 \
  -e MCP_TRANSPORT=streamable-http \
  -e MCP_HOST=0.0.0.0 \
  amazon-bedrock-knowledge-base-mcp:local
```

### Health Endpoints

| Endpoint | Description |
|----------|-------------|
| `GET /health` | Basic health check (always returns 200 if running) |
| `GET /health/ready` | Readiness check (validates AWS credentials via STS) |

---

## Development

```bash
# Clone and install
git clone https://github.com/Zlash65/amazon-bedrock-knowledge-base-mcp.git
cd amazon-bedrock-knowledge-base-mcp
uv sync --group dev

# Run tests
uv run pytest -q

# Type check
uv run pyright

# Lint
uv run ruff check .

# Format
uv run ruff format .
```

---

## Metadata Schema

Schema files define available metadata fields for filtering. See [`schemas/README.md`](schemas/README.md) for examples.

Example schema:

```json
{
  "fields": [
    {
      "key": "x-amz-bedrock-kb-source-uri",
      "type": "string",
      "description": "Source document URI",
      "alias": "source"
    },
    {
      "key": "category",
      "type": "string",
      "description": "Document category",
      "filterable": true
    }
  ]
}
```

Use in queries:

```python
# Using alias
{"where": {"source": "s3://bucket/doc.pdf"}}

# Using direct key
{"where": {"category": ["finance", "legal"]}}
```

---

## Limitations

- Results with `IMAGE` content type are not included in query responses
- Reranking requires additional IAM permissions and is only available in specific regions
- Knowledge bases must be tagged with `KB_INCLUSION_TAG_KEY=true` to be discoverable

---

## License

Apache-2.0 - see [LICENSE](LICENSE) and [NOTICE](NOTICE).

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