"Pix" matching MCP servers:

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Local-first MCP runtime for coding agents with bounded workspace access, content-preconditioned writes, AST search, LSP navigation and diagnostics, and Git status/diff. Designed to give coding agents useful repository access without treating unrestricted shell access as the default integration boundary.

Provides Claude with a persistent, auditable memory stored as markdown and YAML files in a private GitHub repo. Enables reading, appending, organizing, and messaging between agent conversations through MCP tools.

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Orchestrates multiple coding agents at once so an MCP client can delegate implementation work while retaining judgment: each agent runs in its own isolated git worktree and branch, claims the files it edits, and communicates via a mailbox and shared board. Supports blocking questions to the orchestrator, Codex-written acceptance tests locked before workers start, scope validation, and reporting on first-pass success.

Runs git and GitHub CLI commands outside the macOS sandbox to bypass sandbox restrictions like SSH signing and TLS issues.

Enables ChatGPT to securely manage a Raspberry Pi's Kalshi live-recorder project through MCP, including file operations under /srv/kalshi, Git pulls, service control, and health inspection, while deliberately restricting access to the rest of the system.

Enables AI agents to manage version control for product assets with tools for creating change sets, comparing versions, approving merges, and exporting receipts.

MCP server that enables AI agents to perform GitHub operations (repos, issues, commits, PRs) via natural language, integrated with hosts like Antigravity.

Enables humans to review AI-generated code changes through a GUI: agents freeze git diffs and add findings/diagrams, while reviewers annotate and save decisions returned as an exact correction prompt.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.