Teamwork Graph CLI

CodeGraph is a local code-intelligence tool for AI coding agents, distributed as a CLI, MCP server, and embeddable npm library by Colby McHenry. It parses source code into a SQLite knowledge graph of symbols, files, calls, imports, inheritance, dependencies, framework routes, and cross-language bridges, then resolves references and provides full-text search, source context, call paths, callers, callees, impact analysis, and affected-test discovery. Its primary MCP operation, codegraph_explore, returns relevant verbatim source together with relationships and blast-radius information so agents can query structure without file-by-file exploration. A native Rust parsing kernel supports more than 20 languages, with a portable fallback for unsupported platforms or files that fail native parsing. A native file watcher incrementally updates the local graph after changes, while connect-time reconciliation catches edits made between agent sessions. The tool installs and configures MCP integrations for agents including Claude Code, Cursor, Codex CLI, OpenCode, Gemini CLI, and GitHub Copilot; projects are initialized with codegraph init and stored locally under .codegraph. The repository states that the software is MIT-licensed and that telemetry can be disabled.

Graphify is a command-line tool and agent skill that turns a codebase and related project materials—including documentation, SQL schemas, configuration files, PDFs, images, and videos—into a locally queryable knowledge graph. It uses deterministic, local tree-sitter AST parsing for code, while non-code materials can receive a semantic pass from the configured AI assistant or API key; it does not use embeddings or a vector store. Graphify labels graph edges as EXTRACTED when they are explicit in the source or INFERRED when resolved by the tool, and can generate a clickable graph.html visualization, a GRAPH_REPORT.md summary, and a graph.json representation for later queries. The CLI is installed as the graphifyy package, registered with `graphify install`, and invoked through `/graphify` in supported AI coding assistants such as Claude Code, Cursor, Codex, Gemini CLI, and GitHub Copilot. The project is developed by Graphify Labs and provides free, fully local code mapping; its homepage describes a separate Graphify platform available through early access.

Agent Context Workshop is a hands-on workshop resource for building and evaluating context layers for coding agents. It uses selected crates from the Qdrant Rust codebase to extract syntax with tree-sitter, resolve symbols and relationships with rustdoc JSON, store the resulting code knowledge graph in Neo4j, and expose graph tools such as search, blast-radius analysis, and implementor lookup to an agent. The workshop compares graph-based agents with grep-style agents using gold-verified questions, deterministic scoring, cached evaluation results, tool-adoption measurements, and trace inspection. Additional notebooks cover static Python resolution with Griffe and an optional Fenic-and-LLM semantic layer. The GitHub repository maintains the workshop through ordered Jupyter notebooks, typed extraction and graph code, evaluation harnesses, tests, committed Qdrant seed data, and a committed evaluation cache; it is licensed under Apache-2.0.

Multi-Agent Workbench is a local-first browser control room for orchestrating coding agents such as Claude Code, Codex CLI, and generic PTY-based command-line agents. Agents work in task rooms under editable YAML role cards that define permissions, speaking style, and decision boundaries; a rule-driven orchestrator pauses execution and risky commands for human approval, while persistent sessions expose terminal activity and status. The system uses a local event-driven architecture with a React interface, Fastify backend, REST API, server-sent events, agent adapters, an approval service, and a SQLite event store. Every action passes through the API and is recorded in an append-only event log, whose events are projected into timelines, decisions, terminal views, artifacts, and diff views. It also provides task templates, Markdown reports and decision logs, real-time room updates, and configurable risk resolutions. Code-writing agents are intended to use isolated Git worktrees, with diff and patch review before changes reach the main workspace; the repository marks this worktree and merge flow as in progress.

Munder Difflin is a free, open-source desktop multi-agent harness that runs multiple terminal-based AI coding agents as coordinated local agents. It wraps agents including Claude Code, OpenAI Codex, Gemini CLI, Qwen, OpenCode, GitHub Copilot CLI, and custom commands, working with users' existing subscriptions and hourly usage limits. Each agent runs as a real node-pty process and is rendered through xterm.js, while an Electron and React interface displays sessions as avatars on a Pixi.js office floor. A GOD orchestrator called Michael assigns and routes work, adjudicates agent messages, and escalates spending, destructive operations, scope changes, and other configured approvals. Agents coordinate through a local Git-backed hive of plain-file memory, atomic mailboxes, a shared blackboard, and an append-only event log; a markdown-first semantic memory layer supports recall across sessions. Optional Git worktrees isolate parallel agents.