Mcpfilesystem Client
The project describes the usage process of a local LLM server, including starting an OpenAI SDK - compatible model (such as Jan), configuring the .env file, and running a Node application. The focus is on restricting file access permissions through the MCP service.
rating : 2 points
downloads : 18
What is the MCP server?
The MCP server is a locally run AI model service that is compatible with the OpenAI SDK interface specification. It allows developers to call locally deployed large language models (LLMs) through standard APIs. It provides secure file system access control through the Model Context Protocol.How to use the MCP server?
Just three steps: 1) Start the local LLM service through Jan. 2) Configure the .env environment variables. 3) Run the Node.js application. The system will automatically handle model calls and file access permissions.Use cases
Suitable for scenarios that require localized AI capabilities and data security, such as internal enterprise knowledge processing, privacy - sensitive data analysis, and AI application development in restricted environments.Main features
OpenAI SDK compatibilityFully compatible with the OpenAI API specification. Existing code can be migrated to local models without modification.
Tool calling supportThe model must support the tool calling function to handle complex tasks.
Secure file accessPrecisely control the directory scope accessible to the model through the MCP protocol.
Advantages and limitations
Advantages
Process data locally to avoid leakage of sensitive information
Fine - grained file system access control
Seamless integration with the existing OpenAI ecosystem
Limitations
Manual configuration of the local model environment is required
Dependent on specific model functions (tool calling)
The default model may not meet all requirements
How to use
Start the local model service
Use tools like Jan to run an OpenAI - compatible LLM service locally.
Configure environment variables
Modify the .env file to set model parameters, prompts, and the server address.
Run the application server
Start the Node.js service as an API gateway.
Usage examples
Restricted file analysisLet the model only analyze the document content in the specified directory.
Secure data processingProcess local data containing sensitive information.
Frequently Asked Questions
Why is a model supporting tool calling required?
How to add more accessible directories?
What if the default model doesn't work?
Related resources
Jan project official website
Local AI model running environment
OpenAI API documentation
Reference for the compatible API specification
MCP protocol description
File system access control protocol
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