Project Knowledge Mcp

io.github.batook22由 GitHub 账号 batook22 发布v1.0.6更新于 Oct 24, 2026

Cross-project knowledge graph for MCP — map features across mobile, backend, and admin codebases.

已验证STDIO仅桌面知识与记忆开发者工具

概览

AI 生成的概览

保存跨项目的功能知识图谱,让助手能够追踪某个功能在移动端、后端和管理后台代码库之间的流转。

可以做什么
这个本地 MCP 服务器以 JSON 知识图谱保存已注册的项目、功能工作流和跨项目类型映射。工具支持注册与扫描项目、把功能定义为有序步骤、搜索功能/接口/文件/页面、按文件路径反向查找引用、获取带影响分析的步骤上下文、建议与检查类型映射、浏览目录树,以及校验已登记路径是否仍然存在。每次修改后图谱会自动保存,并可提交到版本控制。
适用场景
当一个功能横跨多个独立代码库(例如 React Native 应用、NestJS 后端和 Next.js 管理后台),助手在修改、调试或测试前需要全栈上下文时适用。单一仓库的项目用处不大。
运行要求
需要 Node.js 18 或更高版本以及 npm 9 或更高版本(或 pnpm/yarn);通过 npx 或开发依赖以 stdio 在本地运行。需要兼容 MCP 的客户端。配置通过 --knowledge-file 和项目路径等命令行参数完成;不需要环境变量、API 密钥或账号。
安装前请注意
知识文件是纯 JSON,包含项目路径、功能映射以及扫描得到的文件内容,提交或分享前应视为可能敏感。扫描器据称只读,但注册、删除、导入或自动修复知识的工具会写入知识文件,导入还可能替换已有知识。请让每个 IDE 窗口指向同一个绝对 --knowledge-file 路径,以免图谱被拆散。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Project Knowledge Mcp,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

Project Knowledge MCP Server

[Node.js] [npm] [License]

A cross-project knowledge graph for the Model Context Protocol (MCP). Map features across mobile, backend, and admin codebases so your AI agent has full-stack context when testing, writing code, debugging, or adding features.


Quick Start

bash
npx -y project-knowledge-mcp --knowledge-file ./project-knowledge.json

Then add to your MCP settings:

json
{  "mcpServers": {    "project-knowledge": {      "command": "npx",      "args": [        "-y",        "project-knowledge-mcp",        "--knowledge-file", "C:\\projects\\project-knowledge.json"      ],      "autoApprove": []    }  }}

Table of Contents


Overview

The Problem

When working on a project with multiple codebases — for example, a React Native mobile app, a NestJS backend, and a Next.js admin panel — the AI agent has no awareness of how a single feature flows across all three. This leads to incomplete context, missed dependencies, and breaking changes that could have been caught earlier.

The Solution

This MCP server stores a knowledge graph of your features, mapping each workflow step to the relevant screens, endpoints, controllers, and files in every project. The AI agent can then query this graph to understand end-to-end feature flows, detect cross-project impacts before editing files, and keep type definitions synchronized across codebases.


Features

  • Multi-project awareness — register any number of projects (mobile, backend, admin, etc.)
  • Feature workflow mapping — define features as ordered steps across all projects
  • Auto-scanning — discover NestJS endpoints, Next.js pages, and React Native screens automatically
  • Full-text search — search across features, endpoints, files, and screens
  • Cross-reference lookup — given a file path, find which features reference it
  • Rich context — retrieve all endpoints, screens, and files for a feature at a specific workflow step
  • Breaking change detection — before editing a file, see which other projects will be affected
  • Type/schema synchronization — map equivalent types across projects (e.g., ProductCreateDto ↔ ProductFormSchema)
  • Architecture exploration — browse any project's directory tree with keyword filtering and content highlighting
  • Health validation — verify that all registered file paths still exist; auto-detect stale entries
  • Persistent knowledge — auto-saves to a JSON file after every mutation; can be git-tracked and shared
  • 100% dynamic — all configuration via CLI arguments and runtime tools; no source code edits required

Prerequisites

  • Node.js >= 18
  • npm >= 9 (or pnpm / yarn equivalent)
  • An MCP-compatible client (e.g., VS Code with Cline, any AI-powered IDE)

Installation & Configuration

Install from npm (recommended)

bash
npm install --save-dev project-knowledge-mcp

Or run directly without installing:

bash
npx -y project-knowledge-mcp --knowledge-file ./project-knowledge.json

Build from Source

bash
git clone https://github.com/punic-pillars/project-knowledge-mcp.gitcd project-knowledge-mcpnpm installnpm run build

CLI Flags

All configuration is provided via CLI arguments. No environment variables or configuration files are required.

FlagDescriptionDefault
--backend-pathAbsolute path to the backend project—
--backend-frameworkBackend framework (nestjs, nextjs, react-native, or auto)auto
--backend-nameCustom name for the backend projectbackend
--mobile-pathAbsolute path to the mobile project—
--mobile-frameworkMobile frameworkauto
--mobile-nameCustom name for the mobile projectmobile
--admin-pathAbsolute path to the admin project—
--admin-frameworkAdmin frameworkauto
--admin-nameCustom name for the admin projectadmin
--knowledge-fileAbsolute path to persist the knowledge JSON./project-knowledge.json

MCP Client Configuration

Basic setup — register projects at runtime via tools:

json
{  "mcpServers": {    "project-knowledge": {      "command": "npx",      "args": [        "-y",        "project-knowledge-mcp",        "--knowledge-file", "C:\\projects\\project-knowledge.json"      ],      "autoApprove": []    }  }}

Bootstrap setup — pre-register projects at startup:

json
{  "mcpServers": {    "project-knowledge": {      "command": "npx",      "args": [        "-y",        "project-knowledge-mcp",        "--knowledge-file", "C:\\projects\\project-knowledge.json",        "--backend-path", "C:\\projects\\backend",        "--mobile-path", "C:\\projects\\mobile",        "--admin-path", "C:\\projects\\admin"      ],      "autoApprove": []    }  }}

Knowledge File Management

The knowledge file is a plain JSON file that stores all registered projects, feature workflows, and type mappings. Understanding where it lives is essential for maintaining a consistent knowledge graph.

The Shared File Pattern

If your fullstack projects live in separate directories (e.g., backend/, mobile/, admin/), each IDE window starts the MCP server from a different working directory. Without --knowledge-file, each instance creates its own fragment:

backend/└── project-knowledge.json   ← only backend context
mobile/└── project-knowledge.json   ← only mobile context
admin/└── project-knowledge.json   ← only admin context

This defeats the purpose of cross-project awareness. Always use --knowledge-file with an absolute path to point all IDE windows to the same file:

projects/├── project-knowledge.json   ← single source of truth├── backend/├── mobile/└── admin/

Use the same --knowledge-file path in every IDE window, regardless of which sub-project you have open. All instances read and write to the same file, keeping the knowledge graph complete and consistent.

When the Default Is Safe

The default path (no --knowledge-file) is only safe when you open the monorepo root — the single directory containing all sub-projects:

my-monorepo/              ← open this in your IDE├── project-knowledge.json   ← created here, covers everything├── backend/├── mobile/└── admin/

If your projects are in separate repositories or directories, always use --knowledge-file.

Sharing with Your Team

Since the knowledge file is plain JSON, you can commit it to version control and share it with your team:

bash
# Track the knowledge graphgit add project-knowledge.jsongit commit -m "chore: add project knowledge graph"
# Or keep it localecho "project-knowledge.json" >> .gitignore

Guideline: One fullstack project = one knowledge file. Use --knowledge-file with an absolute path whenever your projects live in separate directories.


Tools Reference

Project Management

ToolDescription
register_projectRegister a project with name, path, and framework
remove_projectRemove a registered project
scan_projectAuto-discover endpoints, screens, or pages from a project

Feature Management

ToolDescription
register_featureDefine a feature with its multi-project workflow steps
remove_featureRemove a feature
get_featureRetrieve full feature details (compact or verbose, with optional health check)

Search & Query

ToolDescription
searchSearch across features, endpoints, files, and screens
reverse_lookupFind all cross-project references to a file (graph-registered + scan-discovered), plus which features reference it
get_contextRetrieve cross-project context for a feature or step (with optional impact analysis)

Type/Schema Synchronization

ToolDescription
register_type_mappingsRegister one or more type mappings (accepts single object or array)
check_type_mappingFind all files across projects that define or reference a type
suggest_type_mappingsAuto-detect potential type mappings by scanning all projects

Architecture Exploration

ToolDescription
get_architectureExplore a project's directory tree with optional filter (path keyword), highlight (content keyword with ★ marker), and showAll (full tree with matches marked)

Validation

ToolDescription
validate_knowledgeCheck all registered file paths for stale entries; optionally auto-fix with fix=true

Persistence

ToolDescription
export_knowledgeConfirm the knowledge file path and trigger an explicit save (auto-persist handles this after every mutation)
import_knowledgeLoad knowledge from a JSON file (merge or replace, with preview)

Usage Walkthrough

This walkthrough demonstrates the core workflow using a real multi-project setup (NestJS backend, React Native mobile, Next.js admin panel). Domain names have been anonymized — "products" instead of "stations", "orders" instead of "reports" — but every command shown was run against actual projects.

Step 1: Register Projects

json
register_project { name: "backend", path: "C:/projects/backend", framework: "nestjs" }register_project { name: "mobile", path: "C:/projects/mobile", framework: "react-native" }register_project { name: "admin", path: "C:/projects/admin", framework: "auto" }

Step 2: Scan Projects

Discover endpoints, screens, and pages automatically:

json
scan_project { projectName: "backend" }scan_project { projectName: "mobile" }scan_project { projectName: "admin" }

The scanners discover 150+ endpoints, 200+ screens, and multiple admin pages across all registered projects.

Step 3: Define a Feature

Register an auth feature — a straightforward flow that touches all three projects:

json
register_feature {  name: "auth",  description: "Authentication flow — login, register, forgot password, email confirmation",  workflow: [    {      step: 1, name: "Login",      description: "User logs in with email and password",      mobile: { screen: "LoginScreen", api: "POST /api/v1/auth/email/login" },      backend: { endpoint: "POST /api/v1/auth/email/login", controller: "AuthController", file: "src/auth/auth.controller.ts" },      admin: { page: "/login", file: "src/pages/Login" }    },    {      step: 2, name: "Register",      description: "User registers a new account",      mobile: { screen: "RegisterScreen", api: "POST /api/v1/auth/email/register" },      backend: { endpoint: "POST /api/v1/auth/email/register", controller: "AuthController", file: "src/auth/auth.controller.ts" }    },    {      step: 3, name: "Email Confirmation",      description: "Confirm email address",      mobile: { api: "POST /api/v1/auth/email/confirm" },      backend: { endpoint: "POST /api/v1/auth/email/confirm", controller: "AuthController", file: "src/auth/auth.controller.ts" }    },    {      step: 4, name: "Forgot Password",      description: "Request password reset",      mobile: { screen: "ForgotPasswordScreen", api: "POST /api/v1/auth/forgot/password" },      backend: { endpoint: "POST /api/v1/auth/forgot/password", controller: "AuthController", file: "src/auth/auth.controller.ts" }    },    {      step: 5, name: "Reset Password",      description: "Reset password with token",      mobile: { screen: "ResetPasswordScreen", api: "POST /api/v1/auth/reset/password" },      backend: { endpoint: "POST /api/v1/auth/reset/password", controller: "AuthController", file: "src/auth/auth.controller.ts" }    }  ],  test_scenarios: [    "Login with valid credentials returns token",    "Login with invalid email returns 401",    "Register with existing email returns conflict",    "Forgot password sends email",    "Reset password with valid token works"  ]}

Step 4: Query Features

Compact mode — get a summary:

json
get_feature { name: "auth" }

Returns: 5 steps, 5 test scenarios, mobile=5 screens, backend=5 endpoints, admin=1 page.

Verbose mode — get full workflow details:

json
get_feature { name: "auth", verbose: true }

Returns all 5 steps with full mobile screens, backend endpoints, controllers, and file paths.

With health check — verify all registered paths exist:

json
get_feature { name: "auth", includeHealth: true }

Returns: Health: 5/5 backend ok, mobile=5/5, admin=1/5, 5 test scenarios.

Step 5: Search and Cross-Reference

Search across the knowledge graph:

json
search { query: "product" }

Returns 100+ results across features, workflow steps, backend mappings, mobile mappings, type mappings, and file contents.

Find cross-project references to a file:

json
reverse_lookup { filePath: "auth.controller.ts" }

Returns:

  • Feature associations: Which features reference this file (steps 1–5 of the auth feature)
  • Graph-registered: 5 exact matches (steps 1–5 of the auth feature, all backend), plus the admin Login page
  • Scan-discovered: All files across all projects that import or reference auth.controller.ts

Step 6: Type Mappings

Register a cross-project type mapping:

json
register_type_mappings {  mapping: {    typeName: "productId",    sourceProject: "backend",    sourceFile: "src/products/infrastructure/persistence/relational/entities/product.entity.ts",    targetProject: "mobile",    targetFile: "app/_types/ProductTypes.ts",    description: "Standardizing productId as numeric INTEGER across all projects"  }}

Check what references a type before changing it:

json
check_type_mapping { typeName: "productId" }

Returns all files across all projects that define or reference productId.

Auto-discover potential type mappings:

json
suggest_type_mappings { limit: 5, confidence: "high" }

Scans all registered projects and finds exact type name matches — returns suggestions with source and target file paths ready to register.

Step 7: Validate and Export

Validate knowledge health:

json
validate_knowledge

Checks all registered file paths across all features and type mappings. Returns a report of existing and missing entries.

Confirm persistence:

The knowledge graph is auto-persisted after every mutation — register_project, register_feature, register_type_mappings, and validate_knowledge with fix=true all write to disk immediately. Use export_knowledge to confirm the file path before committing to version control:

json
export_knowledge

Returns the path to the knowledge file. Git-track this file to share context with your team.


Security

  • Knowledge file is plain JSON — you control where it is stored and who has access
  • No credentials stored — this MCP only stores project paths and feature mappings
  • File scanning is read-only — scanners only read files, never modify them

Contributing

Contributions are welcome. Please open an issue or pull request for any improvements, bug fixes, or feature requests.


License

MIT

来源:README.md,提交 5930c5c

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v1.0.6最新Sep 16, 2026

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