"Publishing deepseek-r1 LLM API as an MCP server and usage instructions" 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 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.

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.

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

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

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.

Enables coding agents to inspect Python applications, research source and target models, and produce reviewable migration plans with evidence gates and evaluation before production code changes.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

MCP server that exposes an AI decompiler via an OpenAI-compatible API, enabling decompilation, explanation, and variable renaming of disassembly for binary analysis.

Bridges local LLMs running in LM Studio with MCP clients like Claude Desktop to perform reasoning and analysis tasks while keeping sensitive data private. It features a suite of tools for local code review, privacy scanning, and content transformation using auto-discovered local models.

MCP server for reviewing code changes using LLMs, supporting Copilot, Ollama, and OpenAI-compatible endpoints.

MCP server that guides LLM security reviews step-by-step, tracking progress and ensuring all assigned source code is read before completing each plan step.

MCP server for DayZ Enforce Script that gives AI coding assistants deep knowledge of the DayZ scripting API with semantic search, code validation, class hierarchy, and reverse call graphs.

MCP server exposing a shared pr-review skill with tools to list, get, run, and evaluate skills, enabling AI assistants to perform code review tasks.

MCP server for angr binary analysis API workflow retrieval. Extracts real API usage patterns from angr's source code and angr-doc examples, then indexes them with semantic search so LLMs can query correct API call sequences.

Processes large files, error logs, and codebase searches locally via Ollama to reduce token consumption in Cursor by up to 80%.

Provides the real exported API surface and type signatures of any npm package, extracted from its published TypeScript declarations, enabling AI coding agents to use functions accurately and avoid inventing nonexistent APIs.

Enables AI assistants to understand and analyze Spring Boot codebases through static analysis, allowing natural language queries about endpoints, classes, dependencies, and architecture without running the application.

Tracks latest versions and breaking changes for popular SDKs, enabling agents to check version updates and potential breaking changes efficiently.

Enables scanning repositories for hardcoded service URLs and clients, and building service-to-service API dependency maps.