"Tor Project" matching MCP servers:

Enables Codex to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events backed by a matching project-record Git commit. Access is scoped to one workspace and project via short-lived, revocable, hash-stored credentials that cannot reach members, keys, deletion, publication, or deployment.

Enables MCP clients to read a project's Git-backed kickoff, acceptance criteria, handoff package, progress, and next step, and to append validated, audited progress events as project records. It provides short-lived scoped credentials and fail-closed tool allowlisting for safe, resumable AI-assisted development.

Enables local Codex sessions to discover the nearest project mcp.json and expose that project’s declared MCP servers and tools through a session-local bridge, without global configuration copying or launch wrappers.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

MCP server that enables AI assistants to run multi-step agent pipelines (e.g., Issue Analyst → Code Writer → Test Runner → PR Opener) from conversations, with support for Devin, shell, Python, and HTTP agents.

Installs once in Claude Code and automatically discovers the nearest project's mcp.json, launching that checkout's declared MCP servers and forwarding their tools, resources, and prompts through a single connection. Each session keeps its own isolated connections, so repositories can ship their own local server manifests without maintaining a global configuration.

Allows AI to interact with Autodesk Revit via the MCP protocol, enabling retrieval of project data and automation of tasks like creating, modifying, and deleting elements.

Hey @roocode community! I'm thrilled to share a project born from my work with Roocode and the vision of an AI-powered development team: the Anubis MCP Server! This system is heavily inspired by Roocode and designed to orchestrate an AI development workflow based on agile methodology. It simulates

Automatically converts any apcore-based project into an MCP server and OpenAI tool provider with zero code changes.

Enables intelligent task management, multi-agent workflows, and cross-IDE project management through the BMAD methodology, with features like time tracking, quality gates, and project templates.

Enables AI coding agents to self-assign, coordinate, review, and ship work through GitHub Projects v2, with AI-powered PRD generation, sprint planning, issue triage, and token-budget enforcement.

Enables coding agents in different editors and MCP clients to share messages, project context, notes, task ownership, handoffs, and advisory file claims through a local SQLite-backed coordination server. Supports MCP stdio, MCP Streamable HTTP, a JSON HTTP API, and a local CLI for multi-project agent collaboration.

Enables AI coding agents and human managers to coordinate work on GitHub Projects v2 through 20 tools and 169 actions for autonomous task checkout, heartbeats, reviews, token budgets, PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines, backed by GitHub-native storage and MCP resources/prompts.

Enables AI agents and human managers to orchestrate GitHub-based project work by self-assigning tasks, coordinating swarms, tracking token budgets, generating PRDs, planning sprints, triaging issues, and materializing tasks as GitHub issues, milestones, and project views.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Enables AI agents to search, fetch, and interactively browse web pages through a fail-closed Tor/VPN-only tunnel, rotate identities, and exchange end-to-end encrypted messages with other agents via MCP.

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Enables any MCP-capable coding agent to share one plain-Markdown project state — goals, tasks, decision logs, and session handoffs — stored in a project's .apm/ directory, with lock-safe concurrent writes and consistency checks that flag stale, blocked, or unowned work. This lets multiple agents and a human CLI resume work across interrupted sessions without a database or external service.

Bridges stdio MCP clients to shared, warm per-project backend instances over streamable HTTP, so repeated client sessions skip cold starts and transparently survive backend restarts. Heartbeat leases, idle-TTL reaping, and per-request deadlines keep per-project instances alive and shared across multiple clients without hanging the caller.

Turns GitHub Projects v2 into an agentic project management layer where AI coding agents self-assign tasks, coordinate via heartbeats, submit work for review, and stay within token budgets. It also provides AI-powered PRD generation, sprint planning, issue triage, and a PRD-to-issues pipeline, all backed by GitHub-native storage with no external infrastructure.