v0.1.0 · Apache 2.0
Enables AI agents to drive policy evaluation over MCP by starting executions, answering policy questions from case evidence, and reading deterministic outcomes with reasoning traces, while the runtime controls which questions are asked and how answers combine.
v0.17.7 · MIT License
Exposes 20 tools over stdio that let coding agents treat any SSH-reachable machine as a local workspace: reading, writing, editing, searching and listing files, running commands and background jobs, driving persistent terminals, and forwarding ports over one pooled connection, with nothing installed on the remote host.
— · MIT License
Lets AI agents turn a UPI QR code plus cart details into a single review-and-pay page link that opens GPay, PhonePe or Paytm pre-filled, so a human pays in one tap. Agents can also poll live payment status and set or confirm it, closing the checkout loop with signed webhooks.
v0.1.0 · MIT License
Enables any MCP-connected agent to drive a browser by reading each page as an indexed action-space table and performing one guarded operation on a numbered target, refusing and refreshing when the page changes instead of retrying selectors.
v3.0.1 · MIT License
Enables MCP-capable coding agents to act as a deterministic technical art director and multi-engine pipeline builder, locking AI-generated 2D/2.5D game assets to consistent camera angles, palettes, rigs, atlases, and exports across Blender, ComfyUI, UniRig, LibreSprite, Godot 4, Unity, and Unreal Engine 5.
v0.9.0 · MIT License
Stores what AI agents learn — thoughts, decisions, session events and repo facts — in PostgreSQL with pgvector and serves it back through versioned MCP tools with hybrid vector-plus-full-text retrieval and budgeted context packs. Enables multiple agents to share one scoped, role-isolated long-term memory, with deliberate promotion of distilled candidates into durable memories.
v0.1.1 · MIT License
Enables agents to capture real browser interactions over CDP, compile them into deterministic replay scripts with parameterized inputs and stored secrets, and execute those workflows with real input events — no page re-reading or LLM in the replay loop. Also emits portable Agent Skills from recorded workflows.