MCP Workspace Server
Click on "Deploy 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., "@MCP Workspace Serversearch for 'TODO' in the workspace files"
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.
MCP Workspace Server
A lightweight Python MCP server that gives AI agents safe, structured access to files inside a controlled local workspace.
Overview
AI agents often need access to project context stored in local files. Giving an agent unrestricted filesystem access introduces unnecessary security risk.
This project uses the Model Context Protocol (MCP) to expose a small set of controlled workspace tools while restricting access to a configured directory.
Related MCP server: Files MCP Server
MCP Tools
The server exposes three tools:
list_workspace_files
Lists the files available inside the configured workspace.
read_text_file
Reads UTF-8 text files with configurable size limits.
search_text
Searches workspace documents and returns matching filenames, line numbers, and text.
Security
The server resolves requested paths against a defined workspace root and prevents path traversal outside that directory.
Additional safeguards include:
Restricted workspace access
Input validation
File-size limits
UTF-8 handling
Path traversal protection
Automated security tests
Project Structure
mcp-workspace-server/
├── src/
│ └── mcp_workspace_server/
│ ├── __init__.py
│ └── server.py
├── tests/
│ └── test_paths.py
├── workspace/
│ └── example.txt
├── pyproject.toml
└── README.mdThis server cannot be deployed
Maintenance
Related MCP Connectors
Securely search and manage workspace context files for AI agents and teams.
Manage files and folders directly from your workspace. Read and write files, list directories, cre…
Artifact store for AI agents — read, write, and search files by path; share by rendered URL.
Persistent docs and memory for AI agents — read, write, organize & search a shared workspace.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceEnables Large Language Models to safely browse and interact with local file systems through secure directory listing, file reading, and content search capabilities. Built with comprehensive security controls and high-performance handling of large directories and files.1-
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to safely explore directories, read files, search content by pattern or filename, and edit files with checksum verification and dry-run preview within sandboxed filesystem access.6 npm75ISC
- FlicenseNot gradedqualityDmaintenanceProvides secure filesystem access for AI assistants with optimizations like file reading limits and depth-limited traversal to improve token efficiency. It enables AI models to read, write, and search files within explicitly allowed directories while automatically skipping large system folders.3-
- AlicenseNot gradedqualityCmaintenanceProvides a secure, constrained filesystem workspace for LLM agents to manage files, notes, and code artifacts via stdio or remote HTTP. It features granular access controls, including extension whitelisting, storage quotas, and immutable paths for safe automated file operations.BSD 3-Clause