Search Results for "mcp" - Page 5
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Showing 139 open source projects for "mcp"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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GenMedia Creative Studio
AI generative media user experience highlighting use of APIs
...It is useful for creators, marketers, developers, and technical teams that want to prototype media-generation experiences using Google Cloud services. The repository also includes experiments and MCP-related materials for connecting generative media capabilities to agent workflows. It is not an officially supported Google product, so it is best treated as a reference implementation and creative sandbox rather than a managed commercial service. -
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MemClaw
Persistent memory for AI agent fleets (OSS)
...The project emphasizes enterprise-style governance, including permissions, tenant isolation, audit trails, visibility scopes, and agent trust tiers. It also supports agent integrations through MCP and OpenClaw-style workflows, making it useful for multi-agent systems that need persistent recall. Its architecture goes beyond a simple vector database by adding rules about who can store, retrieve, and share each memory. caura-memclaw is best suited for teams building AI agents that need long-term memory, controlled sharing, compliance awareness, and safer cross-agent coordination. -
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BlenderMCP
Blender Model Context Protocol Integration
BlenderMCP is a bridge that connects Blender, a 3D modeling and rendering software, with AI systems like Claude through the Model Context Protocol, enabling direct AI-driven interaction with 3D environments. It allows users to control Blender using natural language prompts, effectively turning AI into a co-creator for 3D modeling, scene construction, and asset manipulation. The system establishes a two-way communication channel between Blender and the AI, where commands can be sent and... -
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Agent Stack
Deploy and share agents with open infrastructure
Agent Stack is an open infrastructure platform designed to take AI agents from prototype to production, no matter how they were built. It includes a runtime environment, multi-tenant web UI, catalog of agents, and deployment flow that seeks to remove vendor lock-in and provide greater autonomy. Under the hood it’s built on the “Agent2Agent” (A2A) protocol, enabling interoperability between different agent ecosystems, runtime services, and frameworks. The platform supports agents built in... -
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Timbal
Simple, performant, battle-tested framework for building reliable AI
...Human approval gates can pause runs, preserve their state, and resume them after a process restart. Built-in capabilities cover persistent memory, context compaction, structured outputs, reusable skills, MCP servers, tracing, and evaluations. Applications can run locally, be self-hosted, or be deployed through the Timbal platform with an accompanying API and user interface. -
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Nexent
Zero-code platform for building AI agents from natural language input
...It focuses on a zero-code approach, allowing users to define workflows and agent behavior purely through language prompts, significantly lowering the barrier to entry for AI development. Built on the MCP ecosystem, Nexent integrates a wide range of tools, models, and data sources into a unified environment for agent creation and execution. Nexent supports multi-agent collaboration, enabling multiple intelligent agents to interact and coordinate tasks within complex workflows. It also includes capabilities for data processing, knowledge tracing, and multimodal interaction, allowing agents to work with different input and output formats. ... -
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Agent Reach
Give your AI agent eyes to see the entire internet
Agent Reach is a command-line tool that gives AI agents access to public internet content across multiple platforms. It is designed for agent workflows that need to read and search sources like Twitter, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu without relying on paid platform APIs. The project focuses on giving AI tools broader visibility into social, video, code, and community data through one interface. It can be useful for research agents, automation workflows, competitive... -
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Archon
The knowledge and task management backbone for AI coding assistants
Archon is an open-source “command center” designed to enhance AI coding assistant workflows by giving developers a centralized environment for knowledge management, context engineering, and task coordination across AI agents. It acts as a backend (including an MCP server) that allows different AI coding tools and assistants to share the same structured context, knowledge base, and task lists, improving consistency, productivity, and collaboration across multi-agent interactions. Users can import documentation, project files, and external knowledge so that assistants like Claude Code, Cursor, or other LLM-powered tools work with up-to-date, project-specific context rather than relying on limited prompt memory. ... -
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BackAnt CLI
Let your AI agent create clean, easy to maintain flask backends
...It can scaffold an entire API or extend an existing project by generating a single route or sub-route, so it supports both greenfield development and iterative expansion. BackAnt CLI is also designed to work with coding agents through an MCP server, which allows compatible AI development tools to generate and modify backend code directly from chat-driven workflows. -
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Scrapling
An adaptive Web Scraping framework
...Scrapling combines high performance, memory efficiency, and extensive async support to deliver blazing-fast scraping workflows. With a developer-friendly API, CLI tools, MCP server integration for AI-assisted extraction, and Docker support, it offers a complete solution for modern web scrapers. -
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Kiro Crew
A persistent workspace for development work that self-improves
...Long-running tasks can plan steps, execute them, validate results, retry failures, and resume from saved checkpoints. The system supports subagents, reusable skills, MCP tools, scheduled jobs, reactive webhooks, and installable workflow-specific apps. Users can interact through a desktop app, web dashboard, CLI, or messaging services such as Slack, Discord, Telegram, Teams, and WeChat. Security controls include approvals, sandboxing, sensitive-path protection, credential redaction, deny rules, audit events, and governance policies. -
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GAIA
Proactive personal AI assistant & companion for daily productivity
...Cross-tool memory retains information about people, projects, preferences, and prior conversations so users do not need to repeat context. Integrations cover services such as Gmail, Calendar, Slack, Linear, Notion, WhatsApp, Telegram, and Discord, with support for additional MCP servers. GAIA is available through web, desktop, and mobile interfaces and can also communicate through messaging platforms. The full-stack Nx monorepo includes Next.js, Electron, React Native, FastAPI, LangGraph, bots, voice processing, and Docker-based self-hosting. -
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MAI-UI
Real-World Centric Foundation GUI Agents
...Unlike traditional UI frameworks, MAI-UI emphasizes realistic deployment by supporting agent–user interaction (clarifying ambiguous instructions), integration with external tool APIs using MCP calls, and a device–cloud collaboration mechanism that dynamically routes computation to on-device or cloud models based on task state and privacy constraints. -
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Universal Tool Calling Protocol (UTCP)
Official python implementation of UTCP. UTCP is an open standard
The python-utcp repository is the official Python SDK implementation of the Universal Tool Calling Protocol (UTCP). UTCP is an open, modern standard designed to let AI agents call any tool or API directly—over HTTP, CLI, WebSocket, gRPC, and more—without the overhead of extra wrapper layers or middleware. It leverages a modular, plugin-based architecture built around Pydantic models and separates the core functionality into a lightweight client and extensible protocol plugins, enabling... -
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Claude How-To
A visual, example-driven guide to Claude Code
Claude How-To is a visual, example-driven guide for learning Claude Code. It covers basic concepts, memory, slash commands, hooks, skills, subagents, MCP configuration, plugins, and advanced agent workflows. The project is designed as a practical learning path rather than a simple list of notes. It includes copy-paste templates that users can apply directly to their own projects. The guide also uses diagrams and structured examples to explain not only how features work, but why they matter in a real development workflow. ... -
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Mini Agent
A minimal yet professional single agent demo project
...The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during long, complex tasks. It includes a basic toolset for file-system operations and shell commands, plus integrations with MCP tools such as web search and knowledge graph access. Mini-Agent also comes with “Claude Skills”-style predefined skills for tasks like document processing, design work, and testing, packaged as reusable behaviors that can be invoked by the agent as needed. -
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Microsandbox
Secure local-first microVM sandbox for running untrusted code fast
Microsandbox is an open source platform designed to securely execute untrusted code in isolated environments using lightweight virtualization techniques. It focuses on combining strong security guarantees with fast startup times by leveraging hardware-level microVM isolation instead of relying solely on traditional containers or full virtual machines. It aims to solve the common tradeoffs between speed, isolation, and control that developers encounter when running untrusted workloads. It... -
18
ADR
ADR secures enterprise AI agents through observability
...It captures agent intent, tool activity, and execution traces from coding assistants, internal automations, and customer-facing agents. A normalized sensor layer provides observability across multiple agent tools and operating systems. ADR-Bench supplies more than 300 realistic tasks, 133 MCP servers, and coverage of 17 documented agent attack techniques. Its two-tier detector combines high-recall triage with deeper agentic analysis of suspicious sessions. The repository includes the open-source sensor, benchmark, detector baselines, evaluation workflows, and figure-generation scripts. Prevention and the offline ADR Explorer red-teaming engine are described by the project but are not included in this release. -
19
universal-modder
Point Claude at any game. Skills, tools and the fal MCP
Universal Modder is an agent-oriented toolkit that helps coding assistants investigate and modify PC games the user owns. It works with agents including Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, and OpenCode. The toolkit can identify a game's engine, determine an appropriate modding route, inspect relevant code or assets, build modifications, and test them in the running game. Optional integrations can generate art, 3D assets, audio, and showcase videos. A shared knowledge base... -
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AbletonMCP
Ableton Live Model Context Protocol Integration
AbletonMCP connects AI assistants to Ableton Live through the Model Context Protocol. It enables prompt-assisted music production, session editing, and complete track arrangement from natural-language instructions. The system combines a Python MCP server with an Ableton MIDI Remote Script that exchanges JSON commands through TCP sockets. It can inspect sessions, create MIDI or audio tracks, build clips, insert notes, trigger clips, and control playback. The integration can also search Ableton’s browser, load instruments and effects, change tempo, and construct sections such as intros, drops, breakdowns, and outros. ... -
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Qwen-Agent
Agent framework and applications built upon Qwen>=3.0
Qwen-Agent is a framework for building applications / agents using Qwen models (version 3.0+). It provides components for instruction following, tool usage (function calling), planning, memory, RAG (retrieval augmented generation), code interpreter, etc. It ships with example applications (Browser Assistant, Code Interpreter, Custom Assistant), supports GUI front-ends, backends, server setups. Agent workflow can maintain context / memory to perform multi-turn or more complex logic over time.... -
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OpenMemory
Local long-term memory engine for AI apps with persistent storage
OpenMemory is a self-hosted memory engine designed to provide long-term, persistent storage for AI and LLM-powered applications. It enables developers to give otherwise stateless models a structured memory layer that can store, retrieve, and manage contextual information over time. OpenMemory is built around a hierarchical memory architecture that organizes data into semantic sectors and connects them through a graph-based structure for efficient retrieval. It supports multiple embedding... -
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
...The generated output can be saved to a file, printed to standard output, or copied to the clipboard for immediate use. In addition to the core command line interface, the project also includes a library, Python bindings, and an MCP server. -
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Portia SDK Python
Portia Labs Python SDK for building agentic workflows
portia‑sdk‑python is an open-source Python SDK by Portia Labs for creating reliable, stateful, authenticated multi-agent AI workflows. It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. Designed for production environments, the SDK integrates with local or cloud LLMs (e.g. OpenAI, Anthropic, Mistral, Gemini) and... -
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Code-Graph-RAG
The ultimate RAG for your monorepo
Code-Graph-RAG is an advanced retrieval-augmented generation system designed specifically for understanding and interacting with large, multi-language codebases by transforming them into structured knowledge graphs. It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. This structured approach enables more accurate and context-aware querying compared...
