Mcp Probe Kit

by mybolide

271 downloads

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GitHub

About

mcp-probe-kit is a protocol-level toolkit designed for developers who want AI to truly understand their project's intent. It's not just a collection of 21 tools—it's a context-aware system that helps AI agents grasp what you're building.

Details

Author: mybolide
Downloads: 271
Categories: Other, Developer Tools, Automation, Productivity

- 21 tools for requirements, design, development, quality, and release
- Structured output returning machine-readable JSON
- Delegated Orchestration Protocol with step-by-step execution plans
- 6 workflow orchestration tools for complex development flows
- Requirements clarification mode for unclear specifications
- Template system with auto/guided/strict profiles
- UI/UX Pro Max tools with design system and data sync

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Mcp Probe Kit

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

From the repository

Use directly with npx (npx mcp-probe-kit@latest) or install globally (npm install -g mcp-probe-kit). Configure in your MCP client's JSON settings (e.g., Cursor, Claude Desktop, Cline) by specifying the command and arguments. After configuration, restart the client.

`init_project`

当用户提供一句话需求时使用。基于 Spec-Driven Development 理念，分析需求并生成完整的项目规格文档（需求分析/技术设计/任务拆解）。适合项目初期的需求澄清和规划

`gencommit`

当用户需要生成 Git commit 消息时使用。返回 Conventional Commits 规范说明、步骤、输出模板和示例，供 AI 根据变更内容生成最终 commit message。它不直接代写最终消息，也不应被判定为空结果

`git_work_report`

基于 Git diff 分析生成工作报告（日报/周期报）核心功能： - 支持日报模式（单个日期）和周期报模式（日期范围） - 自动读取指定日期的所有 Git 提交 - 对每个提交执行 git show 获取完整 diff - 使用 AI 分析 diff 内容提取实际工作内容输出格式： - 只输出「工作内容」部分 - 每条以 - 开头，中文，简洁专业 - 格式：做了什么 + 改了哪里/达到什么效果 - 不输出：提交哈希、文件列表、统计数据、风险总结使用示例： - 日报：git_work_report --date 2026-1-27 - 周期报：git_work_report --start_date 2026-2-1 --end_date 2026-2-6

`code_review`

当用户需要审查代码、真实 Git diff 或托管 Plan 的交付一致性时使用。MCP 可确定性收集 changed files、Plan 声明范围、产物、测试、公共契约、架构和 revision 证据；代码语义问题仍由 Agent 审查，不伪装成静态扫描器

`code_insight`

当用户需要基于代码图谱分析调用链、上下文和影响面时使用。默认桥接 GitNexus，支持 query/context/impact 模式；不可用时自动降级并返回原因

`refactor`

当用户需要重构代码、改善代码结构时使用。指南型工具：注入 code/file_path 与重构清单，由 Agent 分析后输出重构计划 JSON；MCP 不自动修改源文件

`gentest`

当用户需要为代码生成单元测试时使用。指南型工具：注入 code/file_path 与测试清单，由 Agent 生成完整测试代码；MCP 不自动生成或运行测试

`workflow`

仅当 Agent 阅读 Skill 和各工具 description 后仍不确定该调用哪个 MCP 时使用的兜底选择指南。workflow 不做自然语言意图识别：scenario=auto（默认）只返回工具选择规则与速查表，不从 intent 猜 firstTool；Agent 根据完整对话自行判断或澄清。若 Agent 已明确场景，可传显式 scenario 获取该场景的确定性 firstTool、phases 和参数提示。同时确保用户项目已存在 .agents/skills/mcp-probe-kit/SKILL.md 与 AGENTS.md 中的 Skill 引用（缺失则自动创建/更新）。

`init_project_context`

生成/更新项目上下文写作计划（delegated）：MCP 写入 AGENTS.md 与 layout.json；project-context 分类文档与 graph-insights 由 Agent 按返回的 plan 落盘。新功能请先 start_feature，修 bug 请先 start_bugfix。

`estimate`

当用户需要估算开发工作量、评估任务时间时使用。估算开发工作量，输出故事点、时间范围（乐观/正常/悲观）、风险点

`check_spec`

校验已落盘的功能规格（docs/specs/<feature_name>/requirements|design|tasks.md）是否完整：检测残留 [填写] 占位、缺失章节、缺 FR/验收标准、FR 未进覆盖矩阵。写完规格后、进入实现前调用；未通过按报告补全后重跑。

`start_feature`

新功能、功能增强、大版本升级或跨模块研发的首选入口。Agent 必须把当前对话已确认的完整目标、范围、模块、阶段和约束汇总到 description；用户只说“继续/开始/往下做”时不得原样透传。默认 spec_layout=auto，复杂多模块或多阶段需求会先生成 parent-child 子规格拆分计划，再进入 add_feature→check_spec→实现。仅在规格布局和子规格已明确、且只需渲染规格模板时才直接用 add_feature。

`start_bugfix`

当用户需要找问题、修 bug、排查异常时使用。默认按 SRC-8（TBP-inspired）编排：收敛边界→真因工作表→修复→测试→记忆沉淀。

`start_onboard`

当用户需要快速上手新项目时使用。编排：生成上下文文档。

`start_ralph`

用于需要多轮小步实现、每轮真实验证和正式收敛的长任务。返回有界 Delegated Plan、每轮 Heartbeat 证据契约和可选前台辅助脚本；不自动运行循环、不创建后台进程。安全停止不等于成功

`interview`

当用户需求不明确、需要澄清需求时使用。需求访谈工具，在开发前通过结构化提问澄清需求，避免理解偏差和返工；生成访谈记录文件供后续 start_feature/add_feature 使用；仅支持 feature 类型

`ui_design_system`

生成可执行的视觉方向，而不是风格标签拼盘。输出核心任务、信息架构、内容密度、排版与色彩策略、组件原则、明确禁用项和截图验收标准。

`ui_search`

搜索页面结构、组件、交互规范和实现参考。新 UI 流程优先使用 structure 模式按任务和页面类型选择信息架构；旧 search/catalog/template 模式继续兼容。

`start_ui`

编排 UI 设计与实现：先锁定视觉方向和信息架构，再生成关键页面，后续通过真实截图评分与迭代完成验收。

`start_product`

产品设计完整工作流入口。返回闭环 delegated plan：Agent 生成 PRD 与原型文档，调用 ui_design_system 和 start_ui 完成设计系统及可交互 HTML 原型，并更新项目上下文；不会引用不存在的 gen_prd/gen_prototype 工具。

`plan_heartbeat`

由 Agent 在 Delegated Plan 执行过程中记录轻量检查点。首次调用必须提供完整 plan；后续合并步骤、证据、产物、候选经验、验收结果、运行证据和 revision。除 requirements 外，每条用于收敛的 evidence 必须至少提供 reference 或 revision，否则 converge 会明确拒绝。只记录状态，不代替 Agent 执行。

`resume_plan`

从 .mcp-probe-kit/plans/ 读取 Delegated Plan 检查点，按依赖计算下一可执行步骤、阻塞步骤和 resumeContext。plan_id 可选；省略时自动恢复当前项目最近更新的 active/blocked Plan。本工具只读取状态，不替 Agent 执行；返回 mustContinue=true 后 Agent 必须立即执行 nextStep/nextTool，逐步调用 plan_heartbeat，禁止只汇报恢复结果后停止。

`converge`

按 Delegated Plan 自己声明的证据和质量闸门关闭计划。任一未完成步骤、未决事项、必需证据或验收结果缺失都会拒绝收敛；除 requirements 外，证据只有摘要但没有 reference/revision 也不算可复核证据。调用参数只能增加证据要求，不能削弱 Plan。

`architecture`

独立架构领域能力，使用 ARC-8 完成架构评估、设计、校验和漂移检查。可直接调用，也可由功能、Bug 或重构流程按需组合；MCP 负责方法、门禁与结构化证据，不替 Agent 声称绝对最优架构。

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "mcp probe kit": {
            "mcp-probe-kit": {
                "command": "npx",
                "args": [
                    "mcp-probe-kit@latest"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-probe-kit": {
        "command": "npx",
        "args": [
            "mcp-probe-kit@latest"
        ]
    }
}

<div align="center">

<h1>知时MCP | mcp-probe-kit</h1>
<p><strong>Know the Context, Feed the Moment.</strong></p>
<p>
<code>Introspection</code> · <code>Context Hydration</code> · <code>Delegated Orchestration</code>
</p>
</div>

---

> Talk is cheap, show me the Context.
>
> mcp-probe-kit is a protocol-level toolkit designed for developers who want AI to truly understand their project's intent. It's not just a collection of 21 tools—it's a context-aware system that helps AI agents grasp what you're building.

> 🚀 AI-Powered Complete Development Toolkit - Covering the Entire Development Lifecycle

A powerful MCP (Model Context Protocol) server providing 21 tools covering the complete workflow from product analysis to final release (Requirements → Design → Development → Quality → Release), all tools support structured output.

🎉 v3.0 Major Update: Streamlined tool count, focus on core competencies, eliminate choice paralysis, let AI do more native work

Supports All MCP Clients: Cursor, Claude Desktop, Cline, Continue, and more

Protocol Version: MCP 2025-11-25 · SDK: @modelcontextprotocol/sdk 1.25.3

---

📚 Complete Documentation

👉 https://mcp-probe-kit.bytezonex.com

- Quick Start - Setup in 5 minutes
- All Tools - Complete list of 21 tools
- Best Practices - Full development workflow guide
- v3.0 Migration Guide - Upgrade from v2.x to v3.0

---

✨ Core Features

📦 21 Tools

- 🔄 Workflow Orchestration (6 tools) - One-click complex development workflows
- start_feature, start_bugfix, start_onboard, start_ui, start_product, start_ralph
- 🔍 Code Analysis (3 tools) - Code quality and refactoring
- code_review, fix_bug, refactor
- 📝 Git Tools (2 tools) - Git commits and work reports
- gencommit, git_work_report
- ⚡ Code Generation (1 tool) - Test generation
- gentest
- 📦 Project Management (7 tools) - Project initialization and requirements management
- init_project, init_project_context, add_feature, estimate, interview, ask_user
- 🎨 UI/UX Tools (3 tools) - Design systems and data synchronization
- ui_design_system, ui_search, sync_ui_data

🎯 Structured Output

Core and orchestration tools support structured output, returning machine-readable JSON data, improving AI parsing accuracy, supporting tool chaining and state tracking.

🧭 Delegated Orchestration Protocol

All start_ orchestration tools return an execution plan in structuredContent.metadata.plan.
AI needs to call tools step by step and persist files, rather than the tool executing internally.

Plan Schema (Core Fields):
``json { "mode": "delegated", "steps": [ { "id": "spec", "tool": "add_feature", "args": { "feature_name": "user-auth", "description": "User authentication feature" }, "outputs": ["docs/specs/user-auth/requirements.md"] } ] }`Field Description: -mode: Fixed as delegated-steps: Array of execution steps -tool: Tool name (e.g. add_feature) -action: Manual action description when no tool (e.g. update_project_context) -args: Tool parameters -outputs: Expected artifacts -when/dependsOn/note: Optional conditions and notes 🧩 Structured Output Field Specification (Key Fields) Both orchestration and atomic tools returnstructuredContent, common fields: -summary: One-line summary -status: Status (pending/success/failed/partial) -steps: Execution steps (orchestration tools) -artifacts: Artifact list (path + purpose) -metadata.plan: Delegated execution plan (only start_

)

-

specArtifacts

: Specification artifacts (start_feature)

-

estimate

: Estimation results (start_feature / estimate)



🧠 Requirements Clarification Mode (Requirements Loop)






When requirements are unclear, use

requirements_mode=loop in start_feature / start_bugfix / start_ui

.  

This mode performs 1-2 rounds of structured clarification before entering spec/fix/UI execution.



Example:

json

{

  "feature_name": "user-auth",

  "description": "User authentication feature",

  "requirements_mode": "loop",

  "loop_max_rounds": 2,

  "loop_question_budget": 5

}





🧩 Template System (Regular Model Friendly)

add_feature supports template profiles, default auto auto-selects: prefers guided when requirements are incomplete (includes detailed filling rules and checklists), selects strict

 when requirements are complete (more compact structure, suitable for high-capability models or archival scenarios).



Example:

json

{

  "description": "Add user authentication feature",

  "template_profile": "auto"

}





Applicable Tools:

-

start_feature passes template_profile to add_feature

start_bugfix / start_ui also support template_profile

 for controlling guidance strength (auto/guided/strict)



Template Profile Strategy:

-

guided

: Less/incomplete requirements info, regular model priority

-

strict

: Requirements structured, prefer more compact guidance

-

auto

: Default recommendation, auto-selects guided/strict



🔄 Workflow Orchestration






6 intelligent orchestration tools that automatically combine multiple basic tools for one-click complex development workflows:

-

start_feature

 - New feature development (Requirements → Design → Estimation)

-

start_bugfix

 - Bug fixing (Analysis → Fix → Testing)

-

start_onboard

 - Project onboarding (Generate project context docs)

-

start_ui

 - UI development (Design system → Components → Code)

-

start_product

 - Product design (PRD → Prototype → Design system → HTML)

-

start_ralph

 - Ralph Loop (Iterative development until goal completion)



🚀 Product Design Workflow

start_product

 is a complete product design orchestration tool, from requirements to interactive prototype:



Workflow:

1. Requirements Analysis - Generate standard PRD (product overview, feature requirements, page list)

2. Prototype Design - Generate detailed prototype docs for each page

3. Design System - Generate design specifications based on product type

4. HTML Prototype - Generate interactive prototype viewable in browser

5. Project Context - Auto-update project documentation



Structured Output Additions:

-

start_product.structuredContent.artifacts

: Artifact list (PRD, prototypes, design system, etc.)

-

interview.structuredContent.mode: usage / questions / record





🎨 UI/UX Pro Max






3 UI/UX tools with

start_ui

 as the unified entry point:

-

start_ui

 - One-click UI development (supports intelligent mode) (orchestration tool)

-

ui_design_system

 - Intelligent design system generation

-

ui_search

 - UI/UX data search (BM25 algorithm)

-

sync_ui_data

 - Sync latest UI/UX data locally



Note:

start_ui automatically calls ui_design_system and ui_search`, you don't need to call them separately.

Inspiration:
- [ui-ux-pro-max-skill](https://github.com/nex

…

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About

Details

Jump to

Setting up with Highlight

From the repository

init_project

gencommit

git_work_report

code_review

code_insight

refactor

gentest

workflow

init_project_context

estimate

check_spec

start_feature

start_bugfix

start_onboard

start_ralph

interview

ui_design_system

ui_search

start_ui

start_product

plan_heartbeat

resume_plan

converge

architecture

Claude Desktop / Cursor

McpServers

📚 Complete Documentation

✨ Core Features

📦 21 Tools

🎯 Structured Output

🧭 Delegated Orchestration Protocol

🧩 Structured Output Field Specification (Key Fields)

🧠 Requirements Clarification Mode (Requirements Loop)

🧩 Template System (Regular Model Friendly)

🔄 Workflow Orchestration

🚀 Product Design Workflow

🎨 UI/UX Pro Max

Install

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`init_project`

`gencommit`

`git_work_report`

`code_review`

`code_insight`

`refactor`

`gentest`

`workflow`

`init_project_context`

`estimate`

`check_spec`

`start_feature`

`start_bugfix`

`start_onboard`

`start_ralph`

`interview`

`ui_design_system`

`ui_search`

`start_ui`

`start_product`

`plan_heartbeat`

`resume_plan`

`converge`

`architecture`