ObjectLens MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ObjectLens MCP Serverlist buckets for my default provider"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ObjectLens MCP Server
A Model Context Protocol (MCP) server that connects Large Language Models (LLMs) to the ObjectLens REST API. This allows AI assistants to browse S3-compatible buckets, search indexed S3 object metadata, and preview object contents directly.
Configuration
The server is configured using environment variables:
Environment Variable | Description | Default |
| Base URL of the ObjectLens REST API |
|
| Username for HTTP Basic Authentication | None |
| Password for HTTP Basic Authentication | None |
Related MCP server: OssHub
Exposed Tools
The server exposes the following tools to the LLM:
list_providers: List configured S3 storage providers.get_default_provider: Get connection details of the default/active provider.list_buckets: List S3 buckets for a specific provider.list_bucket_objects: List or search objects in a specific bucket with prefix and pagination.get_object_metadata: Retrieve detailed metadata (size, content-type, ETag, etc.) of an object.get_object_preview: Read the content/preview of an object (supports text, JSON, CSV, code, etc.).search_objects: Query indexed metadata globally or scoped to a bucket.scan_bucket: Trigger S3 bucket metadata scanning to sync metadata into ObjectLens database.list_activities: Fetch recent activity logs/operations from ObjectLens.
Installation and Run
Run with UV
You can run the server directly using uv:
# From this directory
uv run python server.pyOr run it remotely:
uv run --path /path/to/objectlens/mcp-server/server.pyDocker
Build locally:
Build the Docker image:
docker build -t objectlens-mcp-server .Run the container:
docker run -i --rm \
-e OBJECTLENS_API_URL="http://host.docker.internal:8000" \
objectlens-mcp-serverPull from GHCR:
The image is automatically built and published to GitHub Container Registry (GHCR) on every push to the main branch or when a release tag (e.g., v1.0.0) is published.
To pull and run the pre-built image directly from GHCR:
docker run -i --rm \
-e OBJECTLENS_API_URL="http://host.docker.internal:8000" \
ghcr.io/<github-owner-or-org>/mcp-server:latest(The -i flag is required because the MCP server communicates over standard input/output).
Integration
Claude Desktop
To integrate this server with Claude Desktop, add it to your configuration file:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"objectlens": {
"command": "uv",
"args": [
"run",
"--path",
"/path/to/objectlens/mcp-server/server.py"
],
"env": {
"OBJECTLENS_API_URL": "http://localhost:8000"
}
}
}
}This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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