Alternatives to lfnovo/content-core

🐍 🏠 - A line-oriented text file editor. Optimized for LLM tools with efficient partial file access to minimize token usage.

🐍 🏠 🐧 🍎 - A MCP server for LLDB enabling AI binary and core file analysis, debugging, disassembling.

🐍 - interact with Keboola Connection Data Platform. This server provides tools for listing and accessing data from Keboola Storage API.

MCP server that converts text to speech using the open-weight Kokoro TTS model (kokoro-onnx weights). It generates MP3 files (converting WAV output with ffmpeg) saved to a local folder, with an option to auto-upload them to an S3 bucket, and is configured through environment variables for voice, speed, language, and storage.

Cisco pyATS server enabling structured, model-driven interaction with network devices.

](https://glama.ai/mcp/servers/Battam1111/Myco) 🐍 🏠 🍎 🪟 🐧 - Agent-first cognitive substrate with 18 manifest-driven verbs (germinate / eat / assimilate / sporulate / traverse / immune / molt / …)

MarkItDown is Microsoft's lightweight Python utility for converting files to Markdown for use with LLMs and text-analysis pipelines, and this repository includes the markitdown-mcp package that exposes the converter through MCP. It converts PDF, PowerPoint, Word, Excel, images (EXIF metadata and OCR), audio (EXIF metadata and speech transcription), HTML, text-based formats such as CSV, JSON, and XML, ZIP files, YouTube URLs, and EPUBs, preserving document structure such as headings, lists, tables, and links.

Connect and unify data across various platforms and databases with .

📇 ☁️ 🏠 - AI-powered task management system for AI-driven development. Features PRD parsing, task expansion, multi-provider support (Claude, OpenAI, Gemini, Perplexity, xAI), and selective tool loadi

🐍 - A high-level framework for building MCP servers in Python

The official Python SDK for the Model Context Protocol. With it, developers build MCP servers that expose tools, resources, and prompts to any MCP host, and MCP clients that connect to any MCP server, over the standard stdio, Streamable HTTP, and SSE transports; it requires Python 3.11+, and the optional CLI extra adds the mcp command-line tool (mcp dev, mcp run, mcp install). It is a development library, not a ready-made data server.

MCP server that connects Blender to LLM clients through a Blender addon and a socket-based connection. It lets an AI create, modify, and delete 3D objects, apply materials and colors, execute Blender Python code, and pull in assets from Poly Haven, Sketchfab, and Poly Pizza, with multi-angle views and renders so the model can check its own work.