"Open source MCP servers on Glama and other marketplaces" matching MCP servers:

Enables running Claude Skills locally on your Mac with sandboxed execution, supporting document processing and integration with MCP-compatible AI tools while ensuring data privacy.

MCP server that gives any LLM a managed Docker workspace with live browser, terminal, code execution, document skills, and autonomous sub-agents.

Enables AI agents to control a live Blender session for scene/object manipulation, rendering, code execution, and PolyHaven asset/texture management. It also supports runtime switching among Ollama, LM Studio, llama.cpp, OpenAI-compatible, and Azure backends.

Enables natural language control of Blender 3D through local AI models, allowing MCP clients to create, modify, and render scenes, apply materials, and execute Python code in Blender.

Lets AI agents drive a live Blender session — reading scene and object data, creating, modifying and deleting objects, setting materials, rendering images, executing code, and downloading PolyHaven assets. Prompts flow through a swappable, provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be reconfigured at runtime without restarting.

Enables AI agents to control a live Blender session — inspecting and editing scenes, objects and materials, rendering images, executing code, and pulling PolyHaven assets — through MCP tools. It also routes prompts to a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, or Azure) that can be switched at runtime.

An MCP Server that enables users to interact with Google's On-Demand Scanning API (v1beta1) through natural language, likely providing capabilities for vulnerability scanning and security analysis of containers and artifacts.

Enables AI agents to control a live Blender session via MCP tools for scene and object operations, rendering, code execution, and PolyHaven asset management. It supports provider-agnostic LLM backends that can be configured at startup or switched at runtime.

Enables AI agents to control a live Blender session with scene/object manipulation, rendering, PolyHaven asset tools, and runtime-switchable LLM provider backends.

Enables AI agents to drive a live Blender session over MCP — inspecting scenes, creating, modifying and deleting objects, applying materials, rendering images, importing PolyHaven assets, and executing code — while routing prompts through a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be switched at runtime.

A deployable MCP server for Cloudflare Workers or Azure Functions that provides example tools (time, echo, math), prompt templates for code assistance, and configuration resources. Enables AI assistants to interact with edge-deployed services through the Model Context Protocol.

An MCP Server that enables natural language interaction with the Open Policy Agent REST API, allowing users to manage policies, decisions, and data through conversational interfaces.

Enables GUI automation by executing Python code with instrumented pyautogui, providing MCP-friendly output and inline screenshot delivery.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A server implementation for the Model Context Protocol (MCP) that runs on Cloudflare Workers and supports OAuth login, allowing Claude AI to use custom tools through local or remote connections.

Enables deployment of MCP servers on Cloudflare Workers with OAuth authentication and remote connectivity. Provides a template for creating cloud-hosted MCP servers that can be accessed by Claude Desktop and other MCP clients over HTTP/SSE.

A serverless deployment for Model Context Protocol (MCP) on Cloudflare Workers that enables AI agents to use custom tools without authentication requirements.

A tool that allows deployment of a remote MCP (Model Context Protocol) server on Cloudflare Workers without authentication requirements, enabling connection to AI models through Claude Desktop or Cloudflare AI Playground.

Enables an LLM to orchestrate multiple downstream MCP tools inside one isolated sandbox in a single turn, filtering intermediate results in memory and returning only the final output to cut context tokens.

Enables fully local, end-to-end research automation: reproducing papers from PDF into runnable code and verified artifacts, writing papers section-by-section with LaTeX/PDF/DOCX export, and running an ideate→debate→design→verdict research pipeline—all without an API key.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Facilitates interaction with AWS Bedrock-enabled tools by implementing Anthropic's Model Context Protocol for seamless tool integration and communication.

Provides a controlled escape hatch for director-mode AI agents to run shell commands, write and edit files, execute Python code, supervise detached background jobs, acquire locks, and capture screenshots.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

Lets your AI find the open-source tool it needs on GitHub and install it as an MCP tool, in a sandbox, after you approve. Reads only the folders you grant; no network unless allowed.

Enables AI agents to drive a running Roblox Studio in real time over a single WebSocket, executing whole Luau programs, installing in-engine controllers, hot-patching scripts during live playtests, and receiving errors, assertions and other events as pushes. It also reaches Roblox Open Cloud for the open place and answers visual questions via a vision sidecar, exposing all of this through nine MCP tools.

Enables agents to run constrained optimization loops on local source files, using Step-5-Preview to propose changes while measuring candidates and returning verified patches.

A hub server that connects to and manages other MCP (Model Context Protocol) servers.

yade-mcp connects AI agents to YADE — the open-source discrete element method engine — through the Model Context Protocol. Browse API docs, run simulations, and execute code, all through natural conversation.

Enables AI agents to browse tasks, open sandboxed repository copies, run shell commands, and diagnose CI failures through typed MCP tools.