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Features

The whole pipeline, and the brain underneath it.

From the first discovery question to live MCP memory, every layer is built around one idea: serve context, don't run agents. Here's the full surface.

The pipeline

A funnel that compounds context.

Each step turns a conversation into a more concrete artifact — and every artifact feeds the next.

01 — Discovery

Pressure-test the idea

A streaming discovery chat probes scope, audience, constraints, data and integrations — and records a framework choice.

  • Seeds from onboarding
  • Surfaces one-way-door decisions early
  • Outputs structured requirements + signals
02 — Planning

Approve a real plan

Discovery becomes phases → milestones → tasks with acceptance criteria, plus the decisions and risks behind them.

  • Priority, dependencies, percent-complete
  • Decisions & challenges as a reasoning trail
  • You approve; your agents update tasks live over MCP
03 — Bootstrap

Generate the bundle

A ten-layer bundle assembled in three stages — Copy, Compose, Adapt — tailored to your coding tool.

  • Deterministic floor, one LLM pass on top
  • CLAUDE.md · .cursorrules · AGENTS.md · GEMINI.md
  • Every file version-stamped
The platform

Everything else the brain does.

MCP bridge

An HTTP server that serves project memory and tools to your local Claude Code, Cursor, Codex or Gemini — read tools plus approval-gated writes.

The crew

A coordinator and specialists per project, each with a scoped prompt and allowed tools. Templates versioned and pinned per project.

In-app Planner

A project-scoped assistant at ⌘J that reads and edits tasks, memory and plan — sharing the exact tool registry your MCP client uses.

Live memory

Typed knowledge — facts, decisions, constraints, patterns — compiled into runtime context packs. Relevant signal, not noise.

Provider-neutral Git

A git:* namespace and webhook router. GitHub-native today; GitLab and Bitbucket are class-file drop-ins.

Self-improving

Version-stamped artifacts feed telemetry — which prompts produce bundles humans keep. The foundation for a planner that improves as the platform sees more outcomes.

Guardrails

CI typecheck, lint, tests and deno check on every PR. A Zod contract layer at every hook boundary.

CLI & admin

A repocrew CLI for the terminal, and an admin panel where prompts, templates and scaffolds are edited and version-pinned.

Built differently

Architecture for an agent-native, multi-provider future.

RepoCrew makes a few deliberate calls that compound over time — the kind of decisions that are cheap on day one and brutal to retrofit later.

DimensionTypical PM + Git integrationRepoCrew
Agent surface REST / GraphQL — built for humans wiring integrations MCP-first — git:create_issue is a callable agent verb
Issue link syntax Proprietary prefixes (e.g. TEAM-123) GitHub-native Closes #7 — zero migration friction
Tasks vs issues One concept, conflated Tasks (planning) and issues (collaboration), cleanly separate
Provider model Per-provider integrations with different shapes One git:* namespace, providers are drop-ins
Code requirement Shaped around code teams Git is optional — serves research, content and ops too
Improvement loop Static templates and rules Telemetry-driven planner, built to self-improve

The honest version: mature tools have more polish and feature surface today. RepoCrew's bet is architectural — GitHub-native syntax, MCP-first, and provider-neutrality are the dimensions that compound if the future is agent-native and multi-provider.

Start free

Hand your tool a project it already understands.