v1.0.0 · MIT License
Enables MCP-compatible AI agents to interact with Discord through a local Vencord plugin inside the native desktop client, providing over 30 tools for messaging, server management, roles, moderation, and invites without bot or user tokens in config files.
v0.1.0 · MIT License
Provides a shared, repo-local memory that lets coding agents recall relevant decisions, conventions, gotchas, and open threads, save new entries, coordinate file claims, and cache file summaries across tools and sessions.
v0.2.0 · Apache 2.0
Enables any MCP client to run or join governed Decision sessions through ordinary tool calls, enforcing who may propose, vote, and commit while producing a verifiable binding commitment.
v0.2.1 · MIT License
Enables coding agents on different machines to exchange end-to-end encrypted messages through a shared, self-hosted relay, exposing inboxes, room history, and notifications to Claude Code, Codex, or any MCP client. Peers' messages arrive automatically as clearly framed untrusted data, so collaborators can coordinate without granting tool, file, or command access.
v1.1.0 · MIT License
Enables Antigravity to delegate concrete local coding tasks to Codex CLI with durable sessions, background execution, native chat links, and event-driven receipts.
v1.0.1 · AGPL 3.0
Enables local MCP clients to expose and execute typed tools through a bounded native runtime with Ed25519 admission, per-session budgets, rate limits, schemas, and cached outputs.
v0.2.0 · Apache 2.0
Enables AI clients to coordinate coding agents on the user’s own computers and servers over MCP, connecting to Herdr, Codex app-server, and experimental ZCode/Amp connectors through a self-hosted relay without inbound ports.
— · Apache 2.0
Bridges a selected browser tab's native WebMCP tools to remote MCP clients through a self-hosted Cloudflare Worker, enabling tool discovery and invocation with session-scoped authentication and per-page trust controls.
— · MIT License
Enables MCP clients to drive the 4NEC2 NEC-2 engine for natural-language antenna modeling and simulation, including building Yagi models, calculating impedance/SWR/gain/front-to-back ratio, sweeping frequency, parsing .out files, optimizing geometry, and generating pattern/sweep plots.