DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.

Local-first AI agent runtime with sandboxed sessions, MCP tools, memory, credentials, audit/replay, and a built-in console. Run OpenAI, Anthropic, MiniMax, DeepSeek V4, and OpenAI-compatible models on your infrastructure.

Open-source quantum Agent workspace with a desktop client, Web UI, messaging, Qiskit/MCP tools, and scientific validation

The ultimate 2-way bridge between OpenAI Codex and DSH: bidirectional chat sync, live Skills mount & auto MCP mirroring.

Auditable vision and cross-platform Computer Use runtime for DeepSeek Harness with source-preserving evidence.

Expose DeepSeek Harness agent capabilities as an MCP server, so an external MCP client (e.g. Hermes) can drive Harness to execute coding tasks. Hermes = brain, Harness = arms.

AI Agent runtime authorization & evidence verification — tool-call GuardrailProvider, CCS 7-dimension verification standard, MCP/DSH security scanner, SSRF/command-injection/credential-exfil blocking with Ed25519 signed receipts.

Open-source self-improving QA agent for software teams. A test harness with memory. Write tests in natural language for web and mobile. agent-qa learns from every run, adapts to UI changes, and catches regressions before you ship.

Reverse engineer anything with agents, from app behavior down to native binaries.

DSH plugin: connect to MCP servers, discover tools, and register them for direct model invocation with retry logic and statistics

Desktop automation MCP server — computer use for any AI agent: control screen, windows, mouse/keyboard, and Chrome via Model Context Protocol (stdio)

Git-native slide format, Agent API, CLI, MCP server, and renderer

A universal, atomic library of mathematics and tools for agents to compose them.

TapTap 小游戏开放能力 mcp

Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.

Code intelligence for agents: find the code that matters and keep your context window and tokens lean.