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Bu listing icin henuz AI raporu yok.

SUMMARY

PAPI keeps you in control of what you're building, across every AI tool you use. Docs, install guides, and issue tracker for the PAPI MCP server.

README.md

PAPI

npm @papi-ai/server
MCP Registry
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Cycles shipped
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License

PAPI keeps you in control of what you're building, across every AI tool you and your team use.

AI coding tools are great at writing code and terrible at remembering why. Every new session starts from zero: you re-explain the project, the decisions, the plan. PAPI is the layer that fixes that. It gives your AI assistant structured project memory (plans, builds, reviews, decisions) that persists across sessions, tools, and teammates.

You connect it once. From then on, your assistant starts every session knowing which cycle you're on, what's in flight, and what to do next.

Free to start. The whole plan → build → review → release loop, on up to three projects, no card. Free runs a real project start to finish; it isn't a trial. Pricing.

What this repo is. Documentation, install guides, and the issue tracker. PAPI's engine is closed source and hosted — you connect to it, you don't build it from here. The @papi-ai/server package on npm is the supported local runtime. The contents of this repo are MIT.

Quick start

Let your AI install it. Paste this to your assistant — Cursor, Claude Code, Windsurf, Codex, VS Code, or any other MCP client:

Read https://getpapi.ai/llms.txt and set up PAPI

That's the whole install. Your assistant reads the runbook for whichever tool it's running in and wires up the connection itself. (Same instructions live in this repo as llms.txt and llms-install.md if your assistant can't fetch URLs.)

Then authenticate — this part is yours. PAPI signs in over OAuth, and no AI can click through a browser consent screen for you. Your assistant will tell you exactly where to click; until you do, the server sits at Needs authentication and no tool call will work. This is the step people miss.

Once you're connected, tell your assistant:

Run the setup tool to scaffold this project, then run orient and tell me which cycle this project is on.

Prefer to wire it up yourself?

Every tool takes the same streamable-HTTP endpoint, https://mcp.getpapi.ai/mcp. In Claude Code that's:

claude mcp add --transport http papi https://mcp.getpapi.ai/mcp

then /mcppapiAuthenticate.

Per-tool config for Cursor, VS Code, Windsurf, Codex, and any generic MCP client is in docs/install.md.

What you get

  • plan breaks your goals into a cycle of right-sized tasks, each with a build handoff your assistant can execute directly.
  • build tracks what was built, what surprised you, and what was discovered along the way.
  • review and release close the loop, so every cycle feeds the next plan.
  • strategy reviews every few cycles step back and check direction, not just velocity.
  • A dashboard at getpapi.ai shows your cycles, board, and decisions, so you can see the state of the project without asking.

The methodology is the product: a plan, build, review, release loop your assistant runs with you, with memory that compounds. PAPI has been built with PAPI for 351+ cycles.

How this differs from a tracker

Unlike Linear or Jira, nothing here is maintained by hand. Those boards assume a human writes the ticket and a human reads it. PAPI's board is written and read by your assistant as a side effect of working: starting a build opens the task, finishing it files the report, releasing closes the cycle. You approve the plan and you sign off the review. The ticket admin in between is the part that disappears.

Unlike Taskmaster and other in-repo task files, PAPI's state isn't a file one tool generates once and then drifts from. It's hosted and structured — cycles, build reports, review verdicts, and Active Decisions carrying confidence levels that change as evidence arrives. The same project memory is there from Claude Code, Cursor, VS Code, or Codex, so switching tools doesn't reset your context, and last cycle's learnings are an input to the next plan rather than something you have to remember to mention.

Neither of those is a knock on the tools. They're solving a different problem to the one that breaks every time your assistant opens a fresh window.

Tools

PAPI exposes these MCP tools to your assistant. The whole loop is a handful of calls.

Core loop

  • orient — one call returns the current cycle, what's in flight, and the recommended next action. Run it at the start of every session.
  • setup — scaffold PAPI onto a new project.
  • plan — break goals into a cycle of right-sized tasks, each with a build handoff your assistant can execute directly.
  • build_list — list the current cycle's tasks and their handoffs.
  • build_execute — start a task (creates a branch and handoff) and complete it (records the build report).
  • review_list / review_submit — surface finished builds and record accept / request-changes / reject verdicts.
  • release — merge completed work and roll the cycle forward.

Board and backlog

  • board_view — read the project board and any task.
  • board_edit — change a task's status, cycle, priority, or notes.
  • ad_hoc — record quick work done outside the cycle so it shows in project history.
  • idea — capture a feature, bug, or research note into the backlog.
  • bug — file a bug against the board.

Strategy and intelligence

  • strategy_review — step back every few cycles to check direction, not just velocity.
  • strategy_change — record an Active Decision, with supersede history.
  • zoom_out — a periodic retrospective across many cycles.

Docs and projects

  • doc_register / doc_search — register and find project reference docs.
  • project_list / project_switch / project_create — manage multiple PAPI projects.

Documentation

In this repo:

Doc What it covers
llms.txt The agent runbook — point your AI at this (live version: getpapi.ai/llms.txt)
llms-install.md Per-tool install instructions for AI assistants
docs/install.md Install paths for every supported tool
docs/how-it-works.md Cycles, handoffs, decisions, and how the pieces fit
docs/troubleshooting.md Connection problems, project routing, common fixes

Full documentation on the website — no account needed:

Page What it covers
Quick Start Zero to your first cycle plan in under 5 minutes
Workflow The full plan → build → review → release loop
Concepts Cycles, handoffs, Active Decisions — the vocabulary
Cheat Sheet Every command on one page
Tool Reference Every PAPI MCP tool with parameters and use cases
Troubleshooting Connection and auth first aid
Handbook For teams: reading dashboards, cycle reports, review flow

Community and support

Stuck, or something's broken? Open an issue — there are templates for each case, and the connection problem one is the one to reach for if PAPI won't connect or won't authenticate, which is where people get stuck most:

Star the repo

If PAPI is useful to you, star it. That's the whole ask, and it's how other people building with AI assistants find it.

Links

  • Website and dashboard: getpapi.ai
  • Pricing: getpapi.ai/pricing — free tier, no card
  • What shipped in each cycle: getpapi.ai/changelog
  • Data, access, and what PAPI doesn't have yet: getpapi.ai/trust
  • Licence: the contents of this repo (docs, guides, config examples, Dockerfile) are MIT. That licence covers this repository only — not the PAPI engine, and not the PAPI name or logo, which are trademarks.

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