
AWS MCP Server
The AWS MCP Server integrates FlowHunt with AWS S3 and DynamoDB, enabling AI agents to automate cloud resource management, perform database operations, and hand...

Connect FlowHunt to your AWS S3 buckets for seamless PDF document access, analysis, and automation using the Sample S3 MCP Server.
FlowHunt provides an additional security layer between your internal systems and AI tools, giving you granular control over which tools are accessible from your MCP servers. MCP servers hosted in our infrastructure can be seamlessly integrated with FlowHunt's chatbot as well as popular AI platforms like ChatGPT, Claude, and various AI editors.
The Sample S3 MCP Server is an implementation of the Model Context Protocol (MCP) designed to connect AI assistants and agents with data stored in AWS S3 buckets. By exposing S3 resources as MCP resources and tools, it enables AI-driven workflows to retrieve, manage, and interact with files—specifically PDF documents—stored in S3. This empowers developers and AI tools to perform tasks like listing buckets, enumerating objects, and retrieving documents, directly enhancing productivity and automation in development environments that require access to cloud-based files. The server is particularly useful for enriching AI context with external data, supporting advanced use cases in document analysis, enterprise search, and more.
No information found in the repository regarding prompt templates.
No specific Windsurf setup instructions found.
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%/Claude/claude_desktop_config.json{
"mcpServers": {
"s3-mcp-server": {
"command": "uv",
"args": [
"--directory",
"/Users/user/generative_ai/model_context_protocol/s3-mcp-server",
"run",
"s3-mcp-server"
]
}
}
}
{
"mcpServers": {
"s3-mcp-server": {
"command": "uvx",
"args": [
"s3-mcp-server"
]
}
}
}
Specify AWS credentials using environment variables or the AWS credentials file (see AWS CLI config docs ). Example:
{
"env": {
"AWS_ACCESS_KEY_ID": "your-access-key",
"AWS_SECRET_ACCESS_KEY": "your-secret-key",
"AWS_DEFAULT_REGION": "your-region"
},
"inputs": {}
}
No Cursor setup instructions found.
No Cline setup instructions found.
Using MCP in FlowHunt
To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:
{
"s3-mcp-server": {
"transport": "streamable_http",
"url": "https://yourmcpserver.example/pathtothemcp/url"
}
}
Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “s3-mcp-server” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.
| Section | Availability | Details/Notes |
|---|---|---|
| Overview | ✅ | Basic summary and function from README and repo |
| List of Prompts | ⛔ | No prompt templates found |
| List of Resources | ✅ | S3 PDF document resources |
| List of Tools | ✅ | ListBuckets, ListObjectsV2, GetObject |
| Securing API Keys | ✅ | AWS creds via env vars or config files |
| Sampling Support (less important in evaluation) | ⛔ | Not mentioned |
Based on the information provided and the structure of the repository, the Sample S3 MCP Server is a focused, well-scoped MCP server for S3-based PDF retrieval and management. It covers core MCP primitives (resources, tools), offers clear setup instructions for Claude, and follows good practices for security and licensing. However, it lacks details on prompts, sampling, and support for platforms like Windsurf and Cursor.
I would rate this MCP server a 7 out of 10 due to its clear S3 integration and tool/resource exposure, but with some missing documentation and features for broader protocol coverage.
| Has a LICENSE | ✅ (MIT-0) |
|---|---|
| Has at least one tool | ✅ |
| Number of Forks | 10 |
| Number of Stars | 47 |
Empower your FlowHunt AI agents to retrieve and analyze PDF documents from S3 buckets for smarter workflows and automation.

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