"Using local LLMs for code writing, reviewing, and rule generation" matching MCP servers:

MCP server for Rule.io marketing automation platform. Enables managing subscribers, tags, campaigns, custom fields, and automations through the MCP interface.

Profile-driven MCP server for safely inspecting and changing local Git repositories via a Streamable HTTP endpoint with deny-by-default security.

Content writing toolkit for headline generation, readability scoring, tone analysis, outline building, and plagiarism similarity checking.

Enables fast, token-efficient access to large documentation files in llms.txt format through semantic search. Solves token limit issues by searching first and retrieving only relevant sections instead of dumping entire documentation.

Enables agents to discover the llms.txt index covering any site, fetch its linked documentation pages as markdown, and search across parsed indexes by section heading, link title, and notes.

A generic MCP (Model Context Protocol) server for any Hugo blog, deployed on Cloudflare Workers. It reads your blog's llms.txt and llms-full.txt files and exposes them as structured tools that AI assistants can query to understand your content.

Enables AI-powered image generation using Azure DALL-E 3 and FLUX models with intelligent automatic model selection. Generates stunning photorealistic or creative images directly within LibreChat through simple text prompts.

Enables image and video generation using BigModel AI's CogView and CogVideoX models via MCP, supporting batch image generation and various configuration options.

Provides image generation capabilities for Claude using the Replicate Flux model, allowing users to create images from text prompts with customizable parameters like aspect ratio and output format.

Enables MCP-capable agents to generate and edit images through Gemini or OpenAI, returning an absolute file path instead of image bytes to keep context windows clean.

Enables users to check Google organic, map pack, and local finder positions for keywords across specified locations, returning per keyword/location rows with ratings, competitors, and rank changes. It runs searches from each location via Apify and can track history with a state key.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

A thin MCP server that delegates lightweight tasks from Claude Code or any MCP-compatible client to local or cloud LLMs via LiteLLM, supporting models like Ollama and cloud APIs as subagents.

Generates blog and social media images using Google's Gemini AI with pre-configured platform presets for Ghost, Medium, Instagram, Twitter, LinkedIn, YouTube, and more.

MCP server for E2B code sandbox, enabling creation, management, and execution of code in secure sandboxes using Python and shell commands.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

An MCP server that generates AI agent tools from Postman collections and requests. This server integrates with the Postman API to convert API endpoints into type-safe code that can be used with various AI frameworks.

Exposes structured code generation tools via MCP protocol, enabling users to generate production-grade Python functions, refactor buggy code, and create multi-function modules using local or cloud-based OpenAI-compatible APIs.

Enables text-to-image generation through the ModelScope platform using the Qwen/Qwen-Image model. It supports customizable parameters such as negative prompts, resolution, and sampling steps within MCP-compatible clients.

Enables users to simulate quantum circuits, evolve qubit state vectors, apply gates such as Hadamard and CNOT, perform Born-rule projective measurements with Monte Carlo shot histograms, and run Grover amplitude amplification through MCP-compatible clients.