"deepseek" matching MCP servers:

Local MCP server that provides DeepSeek-powered code review, file analysis, and consultation tools for coding agents, enabling read-only analysis with minimal token overhead.

MCP server that enables Claude Code to delegate tasks to DeepSeek and other LLMs, offering 20 tools for code review, analysis, testing, and code generation.

Lets any MCP-capable AI coding harness route code reviews and codebase questions through DeepSeek's web chat, exposing review, ask, and status tools with read-only repository access by default.

Provides code generation and completion capabilities using the DeepSeek API, with support for tool chaining and cost optimization.

MCP server for DeepSeek AI models (Chat + Reasoner). Supports multi-turn sessions, model fallback with circuit breaker, function calling, thinking mode, JSON output, multimodal input, and cost tracking.

Generates or reviews Git unified diffs via DeepSeek API with local path validation, enabling secure patch suggestions without scanning repositories.

A Node.js-based FastMCP protocol server that integrates DeepSeek AI capabilities for intelligent conversations and code analysis, providing tool invocation abilities through the MCP protocol.

Provides LLM Agents with AI-powered mentorship for code review, design critique, writing feedback, and brainstorming using the Deepseek API, enabling enhanced output in various development and strategic planning tasks.

An intelligent MCP server that automatically generates Conventional Commits style commit messages by analyzing git diffs using LLM providers like DeepSeek and Groq. It enables developers to maintain standardized version history through natural language interactions in supported MCP clients.

Provides local-first project memory and compact engineering context for Codex and DeepSeek Harness, enabling agents to persist and retrieve project-scoped decisions, task checkpoints, and deterministic EIR/1 engineering facts across sessions.

Enables AI agents to consult expert models (Claude, GPT, Gemini, DeepSeek, Z.ai) for technical guidance, code reviews, and architectural advice without switching context.

A brutally honest code review tool powered by DeepSeek-R1 AI and the Model Context Protocol.

An MCP server that audits DeepSeek Harness (DSH) plugins for security threats using static and dynamic analysis. It enables automatic safety reviews of community plugins before installation, detecting risks like credential theft and prompt injection.

Claude Code plugin and MCP server that has a cheap model, DeepSeek V4.1 Flash, review Claude's code for bugs and give second opinions, for under a cent each. Claude keeps writing the code; an optional savings mode delegates well-specified coding work.

Own your sovereign AI model. Domain-specific fine-tuning of open-source LLMs and SLMs with total control and zero infrastructure hassle. Tuning Engines provides specialized tuning agents to tailor top open models to your needs — fast, predictable, fully delivered. Fine-tune Qwen, Llama, DeepSeek, Mistral, Gemma, Phi, StarCoder, and CodeLlama models from 1B to 72B parameters on your data via CLI o

Enables Claude or other MCP clients to offload bounded tasks such as code review, boilerplate, commit messages, and format conversion to local or cloud OpenAI-compatible models, saving tokens and providing a second opinion. It supports endpoints including LM Studio, Ollama, vLLM, OpenRouter, OpenAI, DeepSeek, Groq, and Cerebras.

Enables AI IDEs to chat with, search, explain, refactor, and audit a local codebase without uploading source code, returning answers backed by file-and-line source citations, confidence scores, and severity labels, plus audit and board-ready strategic reports. Runs locally and standalone as an MCP server compatible with Claude, Cursor, Windsurf, and DeepSeek Harness.

Enables Claude Code and other MCP clients to hand bounded work such as code review, boilerplate generation, commit messages, format conversion and embeddings to a local GPU model, LiteLLM router, OpenRouter, or cheaper cloud API like OpenAI, DeepSeek, Groq or Cerebras. Keeps the orchestrating model as architect and reviewer, cutting token spend and providing a second opinion on code.