DevPlan MCP Server

DevPlan MCP Server

Transforms ideas into detailed, executable development plans with built-in verification, lessons learned tracking, and GitHub issue remediation workflows. Guides Claude through structured interviews, plan generation, execution with Haiku agents, and verification with Sonnet agents to maintain context and code quality across sessions.

Category
访问服务器

README

DevPlan MCP Server

License: MIT MCP Cloudflare Workers 21 Tools

Transform ideas into executable development plans — an MCP server that brings the ClaudeCode-DevPlanBuilder methodology to Claude Code.

The Problem: AI coding assistants often lose context, skip steps, or produce inconsistent code across sessions.

The Solution: DevPlan creates detailed, Haiku-executable development plans with built-in verification, lessons learned, and issue remediation workflows.

flowchart LR
    subgraph Planning["📋 Planning"]
        A[Interview] --> B[Brief]
        B --> C[Plan]
    end

    subgraph Execution["⚡ Execution"]
        C --> D[Execute]
        D --> E[Verify]
    end

    subgraph Learning["🧠 Learning"]
        E -->|issues| F[Lessons]
        F -->|improve| C
    end

    subgraph Remediation["🔧 Remediation"]
        G[GitHub Issue] --> H[Parse]
        H --> I[Task]
        I --> D
    end

    style A fill:#e1f5fe,stroke:#0288d1
    style F fill:#fff3e0,stroke:#f57c00
    style G fill:#fce4ec,stroke:#c2185b

Key Features

Feature Description
Inline Methodology All guidance is embedded — no external fetches needed
Haiku-Executable Plans Plans so detailed that Claude Haiku can execute them
Lessons Learned Captures issues from verification and injects them into future plans
Issue Remediation Converts GitHub issues directly into remediation tasks
Tech Conflict Detection Warns about incompatible technology choices
Executor & Verifier Agents Auto-generates specialized agents for your project

Install

claude mcp add devplan --transport sse https://devplan-mcp-server.mike-c63.workers.dev/sse

Or add to ~/.claude/mcp.json:

{
  "mcpServers": {
    "devplan": {
      "type": "sse",
      "url": "https://devplan-mcp-server.mike-c63.workers.dev/sse"
    }
  }
}

Quick Start

You: "Use devplan_start to help me build a CLI tool for managing dotfiles"

That's it. DevPlan will guide Claude through the entire process:

sequenceDiagram
    participant You
    participant Claude as Claude Code
    participant MCP as DevPlan MCP
    participant KV as Lessons KV

    rect rgb(240, 248, 255)
        Note over You,MCP: 📋 Planning Phase
        You->>Claude: "build me a CLI tool"
        Claude->>MCP: devplan_start()
        MCP-->>Claude: inline methodology guidance
        Claude->>You: Interview questions (one at a time)
        You-->>Claude: Answers
        Claude->>MCP: devplan_create_brief()
        MCP-->>Claude: PROJECT_BRIEF.md
        Claude->>MCP: devplan_generate_plan()
        MCP->>KV: fetch lessons learned
        KV-->>MCP: past lessons
        MCP-->>Claude: DEVELOPMENT_PLAN.md + lessons
        Claude->>MCP: devplan_generate_executor()
        Claude->>MCP: devplan_generate_verifier()
    end

    rect rgb(255, 248, 240)
        Note over You,Claude: ⚡ Execution Phase
        loop Each Subtask
            Claude->>Claude: Execute with Haiku agent
            Claude->>Claude: Verify with Sonnet agent
            Claude->>MCP: devplan_update_progress()
        end
    end

    rect rgb(240, 255, 240)
        Note over You,KV: 🧠 Learning Phase
        Claude->>MCP: devplan_extract_lessons_from_report()
        Claude->>MCP: devplan_add_lesson()
        MCP->>KV: store for future projects
    end

    Claude-->>You: ✅ Project complete!

Usage Examples

New Project

"Use devplan_start to help me build [your idea]"

Fix a GitHub Issue

# Get issue JSON
gh issue view 123 --json number,title,body,labels,comments,url > issue.json

# Then tell Claude:
"Use devplan_issue_to_task with this issue to create a remediation plan"

Check Progress

"Use devplan_progress_summary to show me where we are"

Tools

Planning

Tool Purpose
devplan_start Main entry point - guides Claude through the methodology
devplan_interview_questions Get questions to gather project requirements
devplan_create_brief Generate PROJECT_BRIEF.md
devplan_parse_brief Parse existing brief into structured data
devplan_list_templates List project templates (cli, web_app, api, library)

Generation

Tool Purpose
devplan_generate_plan Generate DEVELOPMENT_PLAN.md scaffold
devplan_generate_claude_md Generate CLAUDE.md scaffold
devplan_generate_executor Generate Haiku-powered executor agent
devplan_generate_verifier Generate Sonnet-powered verifier agent

Execution

Tool Purpose
devplan_validate_plan Check plan completeness and structure
devplan_get_subtask Get specific subtask details by ID
devplan_update_progress Mark subtasks complete with notes
devplan_progress_summary Get completion stats and next actions

Lessons Learned

Feedback loop that captures issues from verification and incorporates them into future plans.

Tool Purpose
devplan_add_lesson Capture a lesson from verifier findings
devplan_list_lessons List accumulated lessons by severity
devplan_archive_lesson Archive old lessons without deleting them
devplan_delete_lesson Remove outdated or incorrect lessons
devplan_extract_lessons_from_report Auto-extract lessons from verification reports

Issue Remediation

Convert GitHub issues into structured remediation tasks — perfect for bug fixes and post-release maintenance.

Tool Purpose
devplan_parse_issue Analyze a GitHub issue to extract requirements
devplan_issue_to_task Generate remediation task with subtasks from an issue

Analytics

Tool Purpose
devplan_usage_stats View usage distribution across users (unique users, requests/user, histograms)
flowchart LR
    A["gh issue view 123 --json ..."] --> B[devplan_parse_issue]
    B --> C{Analysis}
    C --> D[Type: bug/feature]
    C --> E[Severity: 🔴🟠🟡🔵]
    C --> F[Components]
    B --> G[devplan_issue_to_task]
    G --> H[DEVELOPMENT_PLAN.md]

    style A fill:#f5f5f5,stroke:#333
    style H fill:#c8e6c9,stroke:#2e7d32

Architecture

graph TB
    subgraph Client["Claude Code"]
        CC[Claude Code CLI]
    end

    subgraph MCP["DevPlan MCP Server"]
        SSE[SSE Endpoint]
        Dash[Dashboard]
        Tools[21 MCP Tools]
        Gen[Plan Generators]
    end

    subgraph Storage["Cloudflare"]
        KV[(KV Storage)]
        DO[Durable Objects]
        SQL[(SQLite per-DO)]
    end

    subgraph Methodology["Reference"]
        GH[GitHub: ClaudeCode-DevPlanBuilder]
    end

    CC <-->|SSE| SSE
    SSE --> Tools
    Tools --> Gen
    Gen --> KV
    Tools --> DO
    DO --> SQL
    SQL -->|cleanup| KV
    Dash --> KV
    Gen -.->|examples| GH

    style CC fill:#e3f2fd,stroke:#1565c0
    style KV fill:#fff3e0,stroke:#ef6c00
    style SQL fill:#e8f5e9,stroke:#388e3c
    style GH fill:#f3e5f5,stroke:#7b1fa2

Storage Strategy

Data Location Rationale
Session metadata SQLite (per-DO) Auto-deleted when DO destroyed
Lessons learned KV Global access across sessions
Aggregated analytics KV Fast dashboard reads
Cleanup schedules DO Alarms Native, reliable triggering

Dashboard & Analytics

DevPlan includes a public dashboard for viewing aggregate usage statistics:

Dashboard URL: devplan-mcp-server.mike-c63.workers.dev/dashboard

API Endpoint: devplan-mcp-server.mike-c63.workers.dev/dashboard/api/stats

The dashboard shows:

  • Summary cards: Total sessions, total tool calls, countries reached
  • Line chart: Sessions and tool calls over the last 30 days
  • Country table: Top 10 countries by session count

Session Tracking & Cleanup

Each MCP session is tracked with metadata stored in SQLite (per Durable Object):

  • Session ID and timestamps (created, last activity)
  • Geographic data (country, region, continent from Cloudflare)
  • Tool call count and transport type (SSE/HTTP)

Automatic Cleanup: Sessions are automatically cleaned up to prevent storage bloat:

  • After 7 days of inactivity, or
  • After 30 days maximum age

When a session expires, its metrics are aggregated to KV storage before cleanup.

Privacy

All analytics are privacy-preserving:

  • No IP storage: Only Cloudflare-derived country/region codes
  • No user identification: Sessions are anonymous
  • Auto-expiration: Daily stats expire after 90 days via KV TTL
  • Public dashboard: Shows only aggregate statistics

Usage Stats via MCP

You can also query usage statistics programmatically:

"Use devplan_usage_stats to show me the last 7 days of usage"

This returns detailed breakdowns including unique users, requests per user, and distribution histograms.

Recent Updates

timeline
    title DevPlan MCP Server - December 2025 / January 2026

    section Week 6
        Session Cleanup : Auto-cleanup after 7d inactivity or 30d max
        Usage Dashboard : Chart.js visualization at /dashboard
        Analytics API : JSON endpoint at /dashboard/api/stats
        SQLite Tracking : Per-session metadata in Durable Objects

    section Week 5
        Usage Dashboard : Public dashboard with aggregate stats
        Session Tracking : Track unique users per day
        Analytics Tool : devplan_usage_stats MCP tool

    section Week 4
        Haiku-Executable Phases : Claude writes complete code, not scaffolds
        Lesson Archiving : Archive old lessons without deletion
        Severity Filtering : Filter lessons by min severity
        Verifier Workflow : Prompts to run verifier at 100%

    section Week 3
        Content Drift Detection : Detects outdated inline guidance
        Inline Methodology : No external fetches needed
        Issue Remediation : GitHub issues → tasks

    section Week 2
        Error Recovery : Executor agent guidance
        Lessons Enhancement : Active feedback loop
        Verifier Agent : Auto-generate verifiers

    section Week 1
        Tech Conflict Detection : Warns on bad combos
        Task Complete Sections : Squash merge workflow

Why DevPlan?

graph LR
    subgraph Without["❌ Without DevPlan"]
        A1[Vague prompt] --> A2[Inconsistent code]
        A2 --> A3[Lost context]
        A3 --> A4[Repeated mistakes]
    end

    subgraph With["✅ With DevPlan"]
        B1[Structured interview] --> B2[Detailed plan]
        B2 --> B3[Haiku executes]
        B3 --> B4[Sonnet verifies]
        B4 --> B5[Lessons captured]
        B5 -.-> B2
    end

    style A4 fill:#ffcdd2,stroke:#c62828
    style B5 fill:#c8e6c9,stroke:#2e7d32
Without DevPlan With DevPlan
Context lost between sessions Plans preserve full context
Inconsistent code quality Haiku follows exact specifications
Same mistakes repeated Lessons learned system prevents recurrence
No verification step Sonnet actively tries to break the code
Bugs found in production Issues caught before release

Development

npm install
npm run dev      # Local development
npm run deploy   # Deploy to Cloudflare Workers

Contributing

Contributions welcome! Please see the ClaudeCode-DevPlanBuilder repo for methodology details.

Community

Love DevPlan? Share your experience with #devplanmcp on social media!

License

MIT


<p align="center"> <b>Built for Claude Code</b><br> <a href="https://modelcontextprotocol.io">Model Context Protocol</a> • <a href="https://workers.cloudflare.com/">Cloudflare Workers</a> • <a href="https://github.com/mmorris35/ClaudeCode-DevPlanBuilder">DevPlanBuilder Methodology</a> <br><br> 💬 <b>#devplanmcp</b> </p>

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选