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PAPI MCP Server

@getpapi

代码仓库主页

基本信息

传输方式

stdio

认证方式

oauth

作者

getpapi

提交者

Cathal o sullivan

关于 PAPI MCP Server

Persistent Adaptive Planning Intelligence - structured loop engineering for AI coding assistants, with memory that persists across sessions, tools, and teammates.

#project-management#planning#ai-coding#claude-code#memory#pm#loop-engineering#cycles

PAPI MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "papi": {
      "url": "https://mcp.getpapi.ai/mcp"
    }
  }
}

PAPI MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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点击上方按钮,直接连接服务器端点实时获取工具列表。

概览

What is PAPI?

PAPI is a Model Context Protocol server that gives AI assistants structured project memory—plans, builds, reviews, decisions—that persists across sessions, tools, and teammates. It is designed for developers and teams who want to keep AI coding tools aware of the project’s current cycle, status, and next steps.

How to use PAPI?

Connect PAPI to your AI tool as an MCP server. The fastest path is Claude Code: run claude mcp add --transport http papi https://mcp.getpapi.ai/mcp. A browser tab opens for sign‑in, then you can run the setup tool to scaffold the project and orient to discover the current cycle. For other tools (Cursor, VS Code, Windsurf, Codex), see docs/install.md.

Key features of PAPI

  • Plan, build, review, and release cycles that persist across sessions.
  • Strategy reviews every few cycles to check direction.
  • Dashboard at getpapi.ai showing cycles, board, and decisions.
  • Memory that compounds—assistant starts every session knowing the project state.
  • Methodology embedded in the product: plan, build, review, release loop.

Use cases of PAPI

  • Give an AI assistant persistent project context so it never starts from zero.
  • Track what was built, what surprised you, and what was discovered in each cycle.
  • Close the loop between cycles so every plan feeds the next.
  • Maintain a shared project memory across multiple AI tools and teammates.

常见问题

1

What does PAPI do that a simple prompt or notes file can’t?

PAPI provides structured, persistent project memory—plans, builds, reviews, and decisions—that your AI assistant reads and writes automatically. It keeps the project state across sessions, tools, and teammates, so you don’t have to re‑explain everything.

2

What are the runtime or dependency requirements?

PAPI is an MCP server. The supported local runtime is the `@papi-ai/server` package on npm. The PAPI engine itself is closed source; this repository is documentation only.

3

Where is my project data stored?

PAPI uses a cloud dashboard at getpapi.ai to show cycles, board, and decisions. The underlying engine is closed source, so data likely lives on PAPI’s infrastructure. For local runs, the `@papi-ai/server` package may handle data locally—consult the documentation.

4

What transport protocols and authentication does PAPI support?

The quick start uses HTTP transport (`--transport http`). Authentication is handled via a browser sign‑in flow. No other transports or auth methods are mentioned in the README.

5

Is PAPI open source?

No. The PAPI engine is closed source. The repository contains only documentation, and the `@papi-ai/server` npm package is the supported local runtime.

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