Open-source alternatives to KiCAD MCP Server

ddgs is a metasearch engine and web content extractor that provides a toolkit for programmatically retrieving search results from DuckDuckGo. It functions as a search API server and a Model Context Protocol server to integrate web search capabilities directly into large language model environments. The project distinguishes itself by aggregating text, image, news, and video results from multiple providers into a single interface. It includes a utility for fetching URLs and converting HTML content into markdown, plain text, or structured data. The system covers a broad range of search capabil

auto-dev is an AI-native software engineering tool and multi-agent development platform designed to automate the entire software development lifecycle. It functions as an autonomous orchestrator that manages AI-driven coding, testing, and infrastructure configuration through declarative agent chains. The project is built on a Kotlin Multiplatform AI framework, allowing agent logic to run across diverse environments and device interfaces. The platform implements the Model Context Protocol to exchange tools and project information with external AI services. It distinguishes itself through the u

This repository contains the comprehensive documentation for a code editor focused on AI-assisted software development and remote development workflows. It covers the implementation of AI agents and language models used for autonomous code generation, large-scale refactoring, and task iteration. The project is distinguished by its deep integration of autonomous AI agents capable of web navigation, application logic validation, and orchestrating multi-step development processes. It provides specialized frameworks for tailoring AI behavior through custom instructions, model context protocols, a

This project is an autonomous workflow engine and orchestration platform designed to coordinate specialized AI agents. It functions as a development framework that manages the end-to-end lifecycle of complex, multi-step tasks, including persona definition, persistent memory management, and the execution of automated coding workflows. By acting as a Model Context Protocol server, it enables standardized communication between development tools and external AI models. The platform distinguishes itself through an event-driven architecture that routes typed messages between agent personas, allowin

jcode is a framework for developing autonomous AI coding agents that automate software development tasks. It functions as an agent orchestrator, tool runtime, and semantic memory engine, enabling the creation of agents that can modify code, run tests, and iterate on their own functionality. The project is distinguished by its use of recursive agent swarming, where a hierarchy of collaborating agents can spawn child agents to decompose complex tasks. It implements a semantic memory system that combines vector-based retrieval with graph-based relationship mapping to maintain context across sess

atopile is an electronic design automation software and hardware description language that enables the definition of electronic circuits and components as code. It functions as a modular electronics framework and a compiler that transforms programmatic circuit definitions into a normalized model and KiCad project files for physical layout. The system distinguishes itself through automated hardware design automation, using a constraint-based value solver to calculate required component values and validate electrical specifications during the build process. It employs a modular approach to hard

This is a software development kit for integrating the Model Context Protocol into Java applications. It serves as a framework for building AI servers and communication layers that exchange prompts, resources, and tool definitions between AI clients and servers. The SDK provides a transport-agnostic communication layer, allowing bidirectional data exchange over standard I/O, HTTP, or Server-Sent Events. It includes a generative AI resource manager for exposing structured data and prompt templates, and a standardized interface for implementing protocol clients and servers. The project covers

mcp-go is a Go implementation of the Model Context Protocol (MCP) providing an SDK and framework for building servers that connect large language model applications to external tools and data sources. It serves as a developer kit for implementing bidirectional communication and structured data exchange between AI clients and servers. The framework enables the creation of executable tools with structured output schemas, reusable prompt templates, and data resource exposure via URI templates. It supports multiple transport layers, including stdio, HTTP, and Server-Sent Events, using a transport

Model Context Protocol is a standardized framework for connecting large language models to external data sources and executable tools. It enables the creation of a universal interface where servers expose tools, resources, and prompts that can be discovered and utilized by various AI clients. The protocol utilizes a JSON-RPC message system that is transport-agnostic, supporting both standard input/output for local processes and HTTP with server-sent events for remote connections. It emphasizes security and control by delegating model sampling to the client to keep API keys secure from servers

The inspector is a diagnostic and validation tool for the Model Context Protocol. It provides an interactive interface and a transport proxy to discover, inspect, and execute the tools, prompts, and resources provided by an MCP server. The project serves as a debugger and compliance tester to verify that server implementations adhere to the protocol specification and JSON-RPC standards. It allows for real-time monitoring of message exchanges and logs between clients and servers across various transport layers, such as standard input/output and Server-Sent Events. The tool covers a broad rang

This project provides a translation layer and set of adapters designed to bridge AI agents with the Model Context Protocol. It functions as an integration layer that allows agents to operate as protocol-compliant servers and enables the conversion of protocol-based tools into formats compatible with agent frameworks and logic graphs. The adapters facilitate tool interoperability by wrapping external protocol tools for use within agent workflows and exposing internal agent capabilities to any client implementing the Model Context Protocol. This creates a communication bridge that supports inte

The Model Context Protocol C# SDK is a library for building clients and servers that implement the Model Context Protocol to integrate AI tools and resources. It provides an AI tool integration framework and a multi-modal content handler to exchange text, images, and binary resources between AI models and external context providers. The SDK utilizes a JSON-RPC communication library to manage bidirectional data exchange. It features a transport-agnostic communication layer that supports standard input and output, HTTP, and in-memory pipes, with specific integration for ASP.NET Core hosting. T

This is a software development kit and framework for implementing the Model Context Protocol in Go. It provides a standardized system for building servers and clients that exchange external resources, proprietary data, and executable tools to provide context for large language models. The SDK includes a JSON-RPC communication library and an integration framework to expose local data, prompt templates, and typed functions to AI models. It enables the development of both protocol servers that provide external context and clients that consume these remote tools and resources. The project covers

This project is a Model Context Protocol server that acts as a programmatic bridge between large language models and private messaging accounts. It provides an automation interface for interacting with WhatsApp by exposing messaging and data retrieval capabilities as tools for AI assistants. The system utilizes browser automation to control the web application interface, allowing for stateful session management to maintain authentication. It enables the transmission of various content types, including plain text, documents, and audio files formatted as voice messages. The server covers conve

gbrain is an agent framework and retrieval-augmented generation system that combines a durable task queue, a git-synced vector store, and a knowledge graph engine. It provides a foundation for building AI agents that interact with structured knowledge bases using the Model Context Protocol. The system synchronizes markdown files from a git repository into a database for high-performance semantic retrieval and creates typed edges between data pages by extracting entity references and wikilinks. It uses a database-backed queue to execute persistent background jobs and tool loops, ensuring relia

This project is a Model Context Protocol server that connects large language models to web scraping and crawling tools. It functions as a bridge, allowing LLM clients to utilize a web crawling engine and scraping utilities to extract and process web data. The server integrates a markdown web converter that transforms dynamic web pages and PDF documents into clean markdown to optimize consumption by AI models. It also provides a browser automation interface for controlling headless sessions and bypassing access restrictions. The system covers broad capabilities including large-scale website d

OpenSandbox is a secure sandbox runtime and containerized code execution engine designed to run AI-generated code and scripts in isolated environments. It serves as a workload orchestrator that prevents host system contamination by utilizing kernel-level isolation to execute arbitrary commands and scripts. The project distinguishes itself by providing a model context server that bridges large language models to the sandbox for performing file operations and system commands. It also includes a remote GUI sandbox that supports browser automation and desktop interfaces via remote access protocol

MoviePilot is a self-hosted media orchestrator and NAS media library automator. It coordinates workflows between downloaders, metadata scrapers, and file systems to automate the discovery, downloading, renaming, and organization of movie and television content. The system functions as an LLM media management agent, allowing users to control subscriptions, searches, and file organization through conversational text commands. It also acts as a Model Context Protocol server, exposing internal media management tools via a standardized interface for external AI clients and agents. The project inc

ECC is an LLM agent orchestration framework and cross-platform AI tooling suite designed to coordinate multi-model workflows. It provides a system for managing specialized agent roles, reusable skills, and structured planning to execute complex software development tasks across different AI-powered code editors. The project distinguishes itself as a Model Context Protocol manager, providing a configuration layer to integrate external servers and audit tool execution. It further implements an agentic security sandbox that restricts sensitive file access and scans for secret leakage to secure a

This project is a Model Context Protocol server that provides large language models with neural web search and webpage content extraction capabilities. It implements a standardized interface to expose research tools and resources to compatible clients. The server integrates a neural search engine to retrieve real-time internet data using semantic embeddings rather than keyword matching. It includes specialized utilities for company intelligence and reasoning-based deep research, enabling the collection and synthesis of organizational data and professional profiles. The system covers a broad

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Cocoindex is a command-line code search engine and indexing tool that combines abstract syntax tree pattern matching and semantic vector embeddings for precise code discovery. It functions locally and integrates with AI coding assistants to automatically retrieve necessary codebase context through standardized communication protocols and persistent background daemon services. The platform employs an asymmetric embedding architecture that generates vector representations using separate parameters for document indexing and search queries. It supports incremental index maintenance by tracking fi

This project is a browser automation toolset and Model Context Protocol server that connects large language models to live browser sessions. It provides a web debugging interface and a quality auditor to facilitate the analysis of document object model structures and browser logs. The system implements a bridge that streams diagnostics into AI-powered editors, allowing for the automated identification of web bugs. It features a data sanitization pipeline that removes cookies and sensitive headers to prevent private information leakage during the analysis process. The toolset covers a range o

EvoScientist is an autonomous AI scientist and multi-agent research framework designed to plan, code, and execute end-to-end scientific research workflows. It functions as an agentic workflow orchestrator that uses a state-machine to coordinate specialized agents through iterative phases of planning, execution, and verification. The system is distinguished by a persistent knowledge graph memory that distills agent interactions into reusable skills and a hub for integrating external tools via the Model Context Protocol. It features a provider-agnostic model layer for switching between language

Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

This project is a server implementation of the Model Context Protocol designed to function as an AI knowledge retrieval tool. It acts as a semantic search engine and web scraping framework that indexes technical documentation from web sources, local files, and archives, making this information directly accessible to AI coding assistants for context-aware research and querying. The system distinguishes itself through a hybrid search architecture that combines vector-based embeddings with full-text retrieval to improve the accuracy of documentation lookups. It features a modular pipeline for co