Maguyva
Maguyva is agent-first code intelligence that gives AI coding tools a ranked map of a repository before they start editing. Teams connect GitHub repositories, and cloud pipelines parse, rank, and index symbols, dependencies, imports, semantic relationships, and cross-file structure, then keep the index current as code changes. Through one remote MCP integration, agents in Claude Code, Cursor, VS Code, Windsurf, Codex, Gemini CLI, and other compatible clients can query the same grounded context without installing a local indexer or changing editors. Its 11 MCP tools combine semantic, structural, graph, and text retrieval across five search modalities, returning ranked results instead of raw grep output. Agents can ask plain-language questions, locate important symbols, find patterns through AST-aware search, trace dependents, identify orphaned code, analyze a change’s blast radius, and assemble task context before touching a file.
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NeuroNest
NeuroNest is an agent-first integrated development environment built for AI engineers, indie hackers, and engineering teams who want to move faster without sacrificing control or privacy.
At its core, NeuroNest orchestrates 110 specialized AI agents organized across 13 collaborative teams — each responsible for a different layer of the software development lifecycle, from planning and architecture to code generation, testing, and deployment. Rather than a single AI assistant answering one prompt at a time, NeuroNest runs a structured multi-agent workflow that mirrors how real engineering teams operate.
NeuroNest is built local-first. All inference runs on your machine using a ZERA optimizer that dynamically selects the most efficient local model for each task — keeping your code private, reducing latency, and eliminating per-token cloud costs. For teams that prefer hybrid setups, cloud model routing is also supported.
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Proof
Proof is an agent-first document editor built for agents and humans to collaborate. It gives teams a shared document where humans and AI can write together, suggest edits, leave comments, and track who wrote what. Every character carries provenance, with a colored gutter showing authorship, so users can distinguish human-written text from AI-written text. When an AI edits a document, Proof creates suggestions like track changes, with insertions and deletions that users can accept or reject one by one. AI agents can also comment on specific text to explain reasoning, ask questions, flag issues, or continue a conversation inside the document. Users can create a document, share the link with agents such as Claude Code, ChatGPT, Codex, or OpenClaw, and collaborate through a shareable workspace instead of passing around .md files. Proof supports use cases such as bug reports, PRDs, implementation plans, research briefs, growth reports, copy audits, strategy docs, memos, proposals, etc.
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Agent Computer
AgentComputer is a cloud-based infrastructure platform designed specifically for running AI agents in isolated, fully functional virtual environments. It provides “cloud computers” in the form of lightweight Ubuntu-based sandboxes that can be provisioned in under a second, allowing developers to quickly spin up, access, and manage environments through a command-line interface. These environments include persistent storage, meaning any installed tools, files, or configurations remain intact across restarts, enabling continuous and stateful workflows. It is built around an agent-first architecture, where AI agents can directly execute tasks within these environments via SSH, eliminating friction between instruction and execution. It includes an integrated AI harness that supports agents such as Claude, Codex, and other coding assistants, enabling collaborative, multi-agent workflows within the same system.
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