v2.0.0 · MIT License
This MCP server connects AI agents to antidetect browser profiles. It enables vision-based element interaction and complex automated workflows within the RATA/GHM Automate v2 ecosystem.
v2.1.47 · MIT License
Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.
v0.1.0 · MIT License
Enables compatible assistants to access a local catalog of 24 software-engineering specialists and tools for listing, retrieving, planning, consulting, and searching approved knowledge over MCP stdio.
v0.2.0 · MIT License
Enables MCP-capable AI agents to invoke 38 deterministic, private, auditable compute tools over stdio, covering PII masking, finance schedules, health, text, units, media, business, gaming, and scheduling without network access or dependencies.
v0.1.0 · MIT License
Enables AI agents to perform real Wolfram Language computation, create and edit native .nb notebooks and figures, export data, and independently verify results through a stdio MCP interface.
v0.2.0 · MIT License
Enables coding agents to surgically harvest licensed upstream code, scaffold adapters behind canonical contracts, audit seams, verify live behavior, and promote or mount proven components while preserving the host architecture.
v0.1.0 · MIT License
Enables agents to look up a library's Context7-compatible ID and fetch its current, version-specific documentation and code examples, optionally focused on a topic and capped at a chosen token budget.
v0.2.0-alpha · MIT License
This MCP server enables AI agents and teams to coordinate through shared inboxes, threaded conversations, attachments, expiring file reservations, prompts, and live notifications, while replaying missed events after restarts.
v0.0.4 · MIT License
Enables an LLM to triage hard-to-extract Vue components by feeding it structured coupling analysis, dependency graphs, and design tokens, then generating decoupling suggestions with before/after code, composable wrappers for store-bound components, and full rewrite-and-extract operations.