"Using llama.cpp and Searxng with local models" matching MCP servers:

A comprehensive MCP server for Jira, Confluence, and Bitbucket that supports both Cloud and Data Center deployments. It provides 136 tools for managing issues, searching documentation, and handling Git workflows like pull requests and pipelines.

MCP server that enables cloud models (like Gemini/Claude) to delegate coding tasks to a local llama.cpp server, preserving cloud usage limits through an AI-powered code review loop.

Enables image generation using Google's Imagen and other AI models through Nexos.ai platform. Supports single and batch image generation with various quality settings and model options.

Enables querying ClickHouse databases using natural language with AI models, supporting multiple providers and access restrictions via per-call allow-lists.

MCP server for read-only forensic analysis of evidence files using local utilities (file, ExifTool, strings, Volatility).

Enables video generation from text prompts and image-to-video using Google Veo AI models via the Gemini API.

Enables Japanese full-text search on local text files using SQLite FTS5 and SudachiPy. Supports indexing directories, searching with morphological analysis, and retrieving ranked results with snippets.

A Python MCP server that provides language models full read/write access to a Node-RED instance through its Admin HTTP API, enabling flow management with structured Pydantic responses and incremental patching.

Bridges Confluence Wiki with Large Language Models, allowing them to search, read, and explore content through automated HTML-to-Markdown conversion. It supports both local stdio and containerized HTTP/SSE transport modes for flexible deployment.

Minimal calculator-focused MCP server with tools, resources, and prompts using TypeScript and Zod validation.

Enables AI assistants to query, analyze, and discover FileMaker database schemas via OData v4, with pandas-powered analytics for efficient data summaries.

Enables AI assistants to render 3D models from OpenSCAD code, generating single views or multiple perspectives with full camera control. Supports animations, custom parameters, and returns base64-encoded PNG images for seamless integration.

AI-powered incident management MCP server that enables investigation, root cause analysis, and response actions for production incidents using mocked data for demo purposes.

Enables local forensic analysis of files by orchestrating system binaries (file, exiftool, strings, Volatility) via safe subprocess execution.

MCP server that generates images using Gemini 3 Pro Image on Vertex AI, with support for reference images, task management, and GCS integration.

Enables non-multimodal models to see images by providing MCP tools for image understanding and OCR, backed by any OpenAI-compatible vision model.

MCP server that lets AI models invoke CLI agents (Gemini, Codex, Claude, OpenCode) as tools — with parallel execution, retries, and structured output parsing.

A Model Context Protocol server built with FastMCP that provides tools for retrieving the current local date and time. It allows LLMs to access precise temporal information directly from the host environment.

A multi-agent RAG MCP server that answers questions from your documents with a human-in-the-loop approval step, using a coordinator, retriever, and synthesizer agents.

Bridges a local AI agent to a Colab session in the browser, enabling code execution and file operations through the Model Context Protocol.