"Guidance on orchestrating new software projects" matching MCP servers:

Project management CLI + MCP server for AI agents. Register projects once, open them anywhere, sync to S3, auto-init git, and wire into the hasna ecosystem.

Enables LLMs to list, open, and close installed software on Windows, macOS, and Linux through natural language.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Enables ChatGPT's web interface to operate a real Mac by executing shell commands and reading or writing files over a reverse SSH tunnel, without installing a client or consuming API quota.

Gives ChatGPT hands-on control of a local machine: reading, patching and executing code in approved project folders, running real interactive processes, managing plans and worker sub-chats, and driving the browser or desktop through user-granted permissions. Every capability is a switch inside an approved-folder sandbox, so nothing runs that the user did not explicitly enable.

Enables ChatGPT to work on a local project by reading and editing files, running shell commands, keeping terminals and desktop sessions open, and splitting work across durable workers whose context persists between tasks. Long-running work can be steered mid-flight, tracked with Goal, and carried into fresh chats via Compact & Resume.

Lets ChatGPT work directly on a local project by reading and editing files, running shell commands and tests, keeping terminals open, and using the user's desktop, all paired with an approved workspace folder. It also splits independent jobs across persistent workers that retain context, while riding the user's existing ChatGPT plan rather than Codex quota.

Centralized MCP server that provides standardized development workflow commands to Cursor AI, auto-detecting project type (Laravel, Next.js, Flutter, Architecture) and offering relevant commands for implementation, testing, and commits.

Runs builds, tests, and benchmarks on a remote compute node via Tailscale and SSH, syncing projects with rsync.

Guides researchers, including those new to BPP, from raw sequence data to a validated control file that has passed a short test run. Wraps BPP command-line tools without running long analyses itself.

Lets Claude manage tmux sessions on Linux — start long-running ML training jobs, check their output, send keystrokes, and kill them.

An enhanced Model Context Protocol filesystem server that fixes common limitations and adds features like glob pattern search, head/tail reading, intelligent file editing with syntax validation, and new tools for delete and command execution.

Enables local forensic analysis of files by orchestrating system binaries (file, exiftool, strings, Volatility) via safe subprocess execution.

Cross-platform MCP server for policy-controlled command execution on Linux and Windows, with no SSH dependency.

Developers: Search your zsh, bash, or fish shell history from Claude Code, Cline, Cursor, Zed, or any MCP client using tools like search_history (full-text with timestamp/CWD/exit code), recent_in_dir, failed_commands, and command_chains for multi-step sequences. Reindex after new activity. Local-only SQLite FTS5 with secrets redacted before storage.

An MCP server providing standardized local environment configuration, scaffolding, and validation workflows for Laravel projects.

Enables creating temporary Quarto projects, writing files into them, rendering documents, and inspecting project output over MCP, while managing reusable metadata defaults.

MCP server for TQS structural engineering CAD/analysis software, enabling Claude to read building models, extract drawing data, run structural processing, and script against the TQS API.

Sandboxed Bash for Agents. Full state capture on every command.

Stateful, structured, safe shell sessions for AI agents, on real infrastructure.