deepseek-mcp-with-MoE
Documentation
DeepSeek MCP Server
An MCP server implementation that provides code generation and completion capabilities using the DeepSeek API, with support for tool chaining and cost optimization.
Features
- Code generation with language-specific support
- Code completion with context awareness
- Code optimization with multiple targets
- Tool chaining for complex operations
- Built-in caching for cost optimization
- TypeScript implementation with full type safety
Tools
1. generate_code
Generate code using DeepSeek API with language-specific support.
{
"name": "generate_code",
"params": {
"prompt": "Write a function that sorts an array",
"language": "typescript",
"temperature": 0.7
}
}2. complete_code
Get intelligent code completions based on existing context.
{
"name": "complete_code",
"params": {
"code": "function processData(data) {",
"prompt": "Add input validation and error handling",
"temperature": 0.7
}
}3. optimize_code
Optimize existing code for performance, memory usage, or readability.
{
"name": "optimize_code",
"params": {
"code": "your code here",
"target": "performance"
}
}4. execute_chain
Execute a chain of tools in sequence, with context passing between steps.
{
"name": "execute_chain",
"params": {
"steps": [
{
"toolName": "generate_code",
"params": {
"prompt": "Create a REST API endpoint",
"language": "typescript"
}
},
{
"toolName": "optimize_code",
"params": {
"target": "performance"
}
}
]
}
}Installation
1. Clone the repository
2. Install dependencies:
npm install3. Build the project:
npm run build4. Configure your DeepSeek API key in the MCP settings file:
{
"mcpServers": {
"deepseek": {
"command": "node",
"args": ["/path/to/deepseek-mcp/build/index.js"],
"env": {
"DEEPSEEK_API_KEY": "your-api-key"
}
}
}
}Usage
The server can be used with any MCP-compatible client. Here's an example using the MCP CLI:
mcp use deepseek generate_code --params '{"prompt": "Write a hello world program", "language": "python"}'Tool Chaining
Tool chaining allows you to combine multiple operations into a single workflow. Each tool in the chain can access the results of previous tools through the chain context.
Example chain:
1. Generate initial code
2. Complete the code with error handling
3. Optimize the final result
{
"steps": [
{
"toolName": "generate_code",
"params": {
"prompt": "Create a user authentication function",
"language": "typescript"
}
},
{
"toolName": "complete_code",
"params": {
"prompt": "Add input validation and error handling"
}
},
{
"toolName": "optimize_code",
"params": {
"target": "security"
}
}
]
}Cost Optimization
The server implements several strategies to optimize API costs:
1. Request caching with TTL
2. Chain result caching
3. Smart prompt construction
4. Metadata tracking for usage analysis
Development
To start development:
npm run devTo clean and rebuild:
npm run rebuildRequirements
- Node.js >= 18.0.0
- DeepSeek API key
- MCP-compatible client
License
ISC
Frequently asked questions
What is deepseek-mcp-with-MoE?
deepseek-mcp-with-MoE is a Model Context Protocol (MCP) server listed in the TrackMCP directory.
How do I install deepseek-mcp-with-MoE?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is deepseek-mcp-with-MoE open source?
Yes — it is hosted on GitHub at https://github.com/sheshiyer/deepseek-mcp-with-moe and has 4 stars.
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