Measure token savings per AI coding agent, optimize context, and share a live local knowledge graph across 16 CLI clients.

A graph-native code repository for AI agents and the people who build with them.

Source-linked CodeGraph exploration, ranked search, and static navigation for coding agents.

Local deterministic memory and safety kernel for AI agents. Replaces vector RAG with STRATA, a cryptographically signed, append-only ledger, so every agent state carries proof. Uses causal_walk engine to trace execution failures back to their root cause, and Operator Lite to block destructive terminal terminal commands before they ever run

Enables AI coding agents to extract structural C# contracts from files and build solution-wide dependency graphs, so they can navigate code and assess change impact without reading entire files.

Enables AI agents to generate studio-grade fashion photography and 4K motion-captured video, perform garment try-ons and background edits, and export creative assets to commerce, productivity, and social platforms.

MindQL queries, hybrid search, and a thought graph - read/write memory for AI agents.

Structural code intelligence for AI agents: real call graphs, blast radius, and change history.

Give an AI a research direction: it runs literature synthesis, gap validation, hypothesis formation and experiment design itself. 267 markdown skills form a research graph: 51 operations built from 216 atomic steps, any order, explicit backtracking; the plan is approved before it runs and interrupted runs resume. npx install, no runtime, no API key

Guarded context compaction for DeepSeek Harness (dsh): the LLM proposes, deterministic guards dispose — eager per-atom shrink (extract/summary/false under verbatim guards) + lazy reference-graph eviction (0-LLM) + byte-exact recall from an append-only log

VCP visual-synesthesia protocol plugin for DeepSeek Harness: render agent HTML output as real UI (cards / KaTeX math / Mermaid diagrams / built-in calligraphy fonts / zero-JS interactions), plug-and-play on any DSH environment

Multi-Agent + Automation Harness: Graph-based Workflows, MCP, Self-Improving Agents. NextJs+React

Own your AI. The native macOS harness for AI agents -- any model, persistent memory, autonomous execution, cryptographic identity. Built in Swift. Fully offline. Open source.

Open-source antivirus for AI agents: block risky tools, secret access, prompt injection, malicious packages, MCP servers, plugins, and skills at runtime.

The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs, and more.

A local-first personal knowledge layer for AI agents. Build evolving knowledge spaces with LLM Wiki, knowledge graphs, and agent workflows.

Shared long-term memory for AI agents: save and recall context as a searchable knowledge graph.

Show the instruction graph your coding agents actually receive.

A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and amnesia. Empower your AI with persistent, graph-like structured memory across any model, session, or tool. Drop-in replacement for OpenClaw.

MCP servers & Graph API for the UniFi suite of applications, Network, Protect, and Access

A local, stdio-based MCP server that lets AI agents create and maintain a brand project through typed tools covering identity, palette, typography, voice, assets and guide chapters, then validate it and export a self-contained, client-facing static guidelines site that can be hosted anywhere.

Enables AI agents to debug Commodore software in a locally running VICE emulator through its text remote monitor, inspecting registers, memory and screens, disassembling code, setting breakpoints and watchpoints, controlling execution, and working with disk images, snapshots and exported graphics. Runs locally over stdio and includes safety guidance for state-changing operations.

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

Enables coding agents to navigate and verify a contract-backed semantic graph of TypeScript backends, inspect change impact, run checks, explain failures, and draft human-reviewable contracts through bounded MCP tools and matching JSON CLI output.