io.github.atef-ataya/depwire
编码与调试by depwire
提供依赖图和 10 个面向 AI 编码的 MCP 工具,支持 TypeScript、Python、JS 与 Go。
什么是 io.github.atef-ataya/depwire?
提供依赖图和 10 个面向 AI 编码的 MCP 工具,支持 TypeScript、Python、JS 与 Go。
README
Depwire
<div align="center"> </div>Your AI doesn't know your architecture. Depwire does.
What makes Depwire different
<p align="center"> <img src="./assets/deterministic_vs_rag_diagram.svg" alt="Depwire deterministic graph vs RAG probabilistic approach" width="680" /> </p>Depwire builds a DETERMINISTIC, NOT PROBABILISTIC dependency graph of your codebase. This is not RAG. There are no embeddings, no similarity scores, no vector databases, no guesses. Depwire uses tree-sitter — the same parser powering GitHub's code intelligence — to extract exact symbol-level facts from every file: every function, every class, every interface, every import and export relationship, across 16 programming languages. When you ask "what breaks if I delete encodeToken in auth/token.ts?", Depwire does not search for similar-looking code and estimate an answer. It traverses the exact dependency graph and returns the precise list of 14 files that import that symbol, which import chains break, and what your health score drops by. This is compiler-level precision applied to AI-assisted development — not a language model's best guess about your code.
Not a build graph either. Tools like Nx, Turborepo, and Grapher track package-level dependencies for build caching. Depwire tracks symbol-level dependencies — every function, class, and import relationship — which is what makes What If simulation, graph-aware security scanning, and exact blast radius analysis possible.
Contents
- What makes Depwire different
- Start here
- The infrastructure layer
- What If simulation
- Security scanner
- Pre-action verification
- Structural diff between commits
- MCP server — AI integration
- Cross-language edge detection
- Architecture health score
- Language support
- SDK
- Cloud dashboard
- GitHub Action — PR Impact Analysis
- Depwire Action Token (DAT)
- Roadmap
Depwire is the infrastructure layer between your AI coding assistant and your codebase. Before your AI touches a single file, Depwire has already mapped every connection, scored every risk, and simulated every change.

⭐ If Depwire saves you from a broken build, star the repo — it helps this project grow.
The problem
AI coding tools are getting smarter. But they still have a fundamental blind spot: they don't know your architecture before they touch it.
You ask Claude to delete a utility file. It deletes it cleanly. Confident. No warnings.
Then you run the build. 30 files broken.
Claude had no idea. It saw one file. It didn't see the 30 downstream consumers.
This isn't a model problem. It's a context problem. The AI is flying blind.
The infrastructure layer
Depwire is the context and safety layer for AI-generated code.
Depwire sits between your AI and your codebase. It builds a complete dependency graph using tree-sitter — deterministic, not probabilistic — and serves it to your AI through 23 MCP tools.
Four guarantees:
- Local — everything runs on your machine. No cloud parsing. No data sent anywhere.
- Secure — your code never leaves your machine. The security scanner requires no API key.
- Token-efficient — Depwire serves pre-computed graph data. Your AI gets surgical answers, not file dumps. 40% fewer tool calls. 56% fewer file reads.
- Deterministic — tree-sitter parses your code the same way every time. 100% accurate. Not a guess.
Start here
npm install -g depwire-cli
Three commands to understand any codebase:
depwire whatif # know what breaks before you change anything
depwire security # catch vulnerabilities before AI ships them
depwire viz # see your entire architecture instantly
Tested on real-world projects
| Project | Language | Files | Symbols | Edges | Health |
|---|---|---|---|---|---|
| google/guice | Java (multi-module, 13 modules) | 647 | 30,592 | 10,081 | 31/100 |
| honojs/hono | TypeScript | 352 | 6,462 | 2,194 | 41/100 |
| apache/commons-lang | Java (single-module) | 624 | 29,723 | 9,037 | — |
| pallets/flask | Python | 79 | 2,005 | 851 | — |
| dart-lang/shelf | Dart | 108 | 1,639 | 219 | — |
| rstudio/plumber | R | 197 | 1,194 | 219 | — |
Numbers from real
depwire parseruns on public repositories. Last validated: v1.7.1 (June 2026).
What If simulation
Know the blast radius before you touch anything.
depwire whatif . --simulate delete --target src/utils/encode.ts
Real output on honojs/hono — 352 files, 6,245 symbols:
Health Score: 41 → 41 (+0 → unchanged)
Affected Nodes: 29
Broken Imports: 30
• src/utils/jwt/jwt.ts imports decodeBase64Url
• src/adapter/aws-lambda/handler.ts imports encodeBase64
• src/utils/basic-auth.ts imports decodeBase64
[27 more...]
Removed Edges: 32
Before touching a single file. Zero file I/O. Pure in-memory simulation.
Five operations:
depwire whatif . --simulate delete --target src/utils/encode.ts
depwire whatif . --simulate move --target src/utils/encode.ts --destination src/core/encode.ts
depwire whatif . --simulate rename --target src/utils/encode.ts --destination src/utils/encoder.ts
depwire whatif . --simulate split --target src/services/auth.ts --symbols "validateToken,refreshToken"
depwire whatif . --simulate merge --target src/utils/helpers.ts --merge-target src/utils/formatters.ts
Run without --simulate to open the browser UI — side-by-side arc diagrams showing current vs simulated state.
Cross-module dependency intelligence
For multi-module Maven and Gradle projects, Depwire resolves imports across module boundaries — not just within a single module.
Example: simulating deletion of Injector.java in google/guice (a 13-module Java DI framework):
$ depwire whatif . --simulate delete --target core/src/com/google/inject/Injector.java
Action: DELETE core/src/com/google/inject/Injector.java
Affected Nodes: 128
Broken Imports: 124 (cross-module: 106 across 10 extension modules)
Without this, your AI agent has no visibility into cross-module blast radius. With it, dangerous changes are caught before they happen.
Supported build systems:
- Maven (
pom.xmlwith<modules>declarations, recursive nested modules) - Gradle (
settings.gradle/settings.gradle.ktswithinclude()declarations)
Both standard (src/main/java) and non-standard (src/) source layouts are supported.
Security scanner
AI will confidently ship vulnerable code. Depwire stops it before production.
depwire security . # full repo scan
depwire security . --target src/auth.ts # single file
depwire security . --format sarif # GitHub Security tab integration
depwire security . --fail-on high # CI gate — exit 1 if HIGH or above
depwire security . --class secrets # specific check only
Real output on honojs/hono:
6 Critical 19 High 14 Medium 1 Low
10 check categories — dependency CVEs, process safety, credential management, path safety, authentication safety, input validation, information disclosure, cryptography weaknesses, output encoding safety, and architecture-level risks.
Graph-aware severity: a medium-severity finding reachable from an MCP tool or HTTP route is automatically elevated to critical. This is what no generic SAST tool can replicate — Depwire knows your architecture, so it knows what's actually reachable.
Available as MCP tool security_scan and via depwire-cli/sdk.
Pre-action verification
Verify a proposed change is safe before applying it. Checks broken imports, new circular dependencies, health score regression, and security findings in one pass.
depwire verify-change --file src/auth.ts --content-from new-auth.ts
depwire verify-change --diff changes.patch
depwire verify-change --file src/auth.ts --content-from new-auth.ts --json
cat new-auth.ts | depwire verify-change --file src/auth.ts
Example output:
Verify Change Report
──────────────────────────────────────────────────
✗ UNSAFE — risk: high
──────────────────────────────────────────────────
Health Score: 62 → 59 (-3)
Broken Imports: 2
• src/index.ts — missing trackCommand
• src/server.ts — missing handleAuth
New Circular Deps: 0
Security Findings: 1
• [HIGH] Hardcoded secret detected (src/auth.ts:14)
Blast Radius: 8 files affected
──────────────────────────────────────────────────
CI integration:
depwire verify-change --diff pr.patch --fail-on-warnings --quiet
# exits 1 for medium risk, 2 for high risk
Available as MCP tool verify_change and CLI command depwire verify-change.
Structural diff between commits
Compare the dependency graph between any two git refs — branches, tags, commit hashes, HEAD~N.
depwire diff main feature/auth-refactor
depwire diff HEAD~5 HEAD --verbose
depwire diff v1.5.0 v1.6.0 --json | jq
Example output:
Depwire diff: v1.5.0..v1.6.0
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Symbols
+ 114 added VerifyChangeOptions, verifyChangeCommand, input ...
- 66 removed VerifyChangeInput, BrokenImportEntry, CircularDepEntry ...
~ 47 modified __filename, __dirname, packageJsonPath ...
Edges
+ 31 added
- 9 removed
Files
152 → 154 (+2 / -0)
Blast radius: 4 files affected
Health score: 67 → 67 (+0) [D → D]
Security: 1 new / 1 fixed
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Deterministic. No LLM. Safe — uncommitted changes are stashed and restored even if the command errors.
Options: --json (machine-readable), --verbose (every symbol/edge by name), --no-security / --no-health (faster runs).
Visualization

depwire viz
Interactive arc diagram of your entire codebase. Every file, every connection, every dependency visible at once. Hover to inspect. Click to filter. Export as PNG or SVG.
Temporal graph

depwire temporal
Watch your architecture evolve over git history. Timeline slider scrubs through commits — the arc diagram morphs as your codebase grew, coupled, and refactored. Nobody else does this.
All commands
| Command | Description |
|---|---|
depwire viz | Interactive arc diagram in browser |
depwire whatif | Simulate changes before touching code |
depwire verify-change | Verify a proposed change is safe — broken imports, health delta, security |
depwire security | Scan for vulnerabilities — graph-aware severity |
depwire health | 0-100 architecture health score across 6 dimensions |
depwire dead-code | Find unused symbols with confidence scoring |
depwire docs | Generate 13 architecture documents |
depwire temporal | Visualize architecture evolution over git history |
depwire parse | Parse and export dependency graph as JSON |
depwire diff | Structural diff between two git commits — symbols, edges, health, security |
depwire mcp | Start MCP server for AI coding assistants |
All commands auto-detect your project root. No path configuration needed.
MCP server — AI integration
Connect Depwire to any MCP-compatible AI tool. Your AI gets 23 tools it can call autonomously.
Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"depwire": {
"command": "npx",
"args": ["-y", "depwire-cli", "mcp"]
}
}
}
Cursor — Settings → Features → Experimental → Enable MCP → Add Server:
- Command:
npx - Args:
-y depwire-cli mcp

23 MCP tools
| Tool | Description |
|---|---|
connect_repo | Connect to any local project or GitHub repo |
get_architecture_summary | High-level project overview |
get_file_context | Full context — imports, exports, dependents. Includes cross-language connections. |
get_dependencies | What does a symbol depend on? |
get_dependents | What depends on this symbol? |
get_symbol_info | Look up any symbol's details |
search_symbols | Find symbols by name across the codebase |
list_files | List all files with stats |
impact_analysis | What breaks if you change a symbol? Cross-language edges included. |
visualize_graph | Generate interactive arc diagram |
get_health_score | 0-100 health score with recommendations |
find_dead_code | Symbols defined but never referenced |
get_project_docs | Retrieve auto-generated codebase documentation |
update_project_docs | Regenerate documentation on demand |
get_temporal_graph | Architecture evolution over git history |
simulate_change | Simulate move/delete/rename/split/merge before touching code. Returns health delta, broken imports, affected nodes. Cross-language edges included. |
security_scan | Scan for vulnerabilities with graph-aware severity elevation. No API key required. |
verify_change | Safety report before applying code changes. Returns broken imports, circular deps, health delta, affected files. Also available as depwire verify-change CLI. |
claim_files | Multi-agent coordination: declare intent to modify files so other clients avoid conflicts. |
release_files | Release a previously made file claim. |
get_active_claims | Query who is currently working on what. |
record_decision | Save a structured decision for future sessions to reference. |
get_decisions | Retrieve past decisions by query, session, file, or tag. |
.depwire/ runtime state
The coordination tools (claim_files, release_files, get_active_claims, record_decision, get_decisions) write runtime state to .depwire/claims.jsonl and .depwire/decisions.jsonl. Add these to your project's .gitignore:
.depwire/claims.jsonl
.depwire/decisions.jsonl
Cross-language edge detection
Depwire detects connections between files written in different languages.
A TypeScript fetch('/api/users') call matched to a Python @app.get('/api/users') route definition — that's a cross-language edge. Delete the Python route and Depwire shows the TypeScript callers as broken.
Supported patterns:
- REST API edges — fetch/axios calls matched to Express, FastAPI, Flask, Gin route definitions
- Subprocess edges — execSync/subprocess.run calls matched to target files in the graph
These edges flow through every existing feature: What If simulation, impact analysis, security scanner, and arc diagram visualization.
Architecture health score
depwire health .
Overall: 68/100 (Grade: D)
Coupling 70 C
Cohesion 80 B
Circular Dependencies 100 A
God Files 40 F
Orphans & Dead Code 20 F
Dependency Depth 60 D
6 dimensions. Letter grades. Actionable recommendations. Trend tracking across runs.
Note on v1.6.1 scoring change: The dead code scoring methodology was corrected in v1.6.1 to only count exported symbols with zero dependents as candidates for dead code. Previously, local variables and class internals were incorrectly included, inflating dead code ratios for codebases with internally-complex modules. Health scores from v1.6.1+ are not directly comparable to scores from earlier versions.
SDK
Depwire exposes a stable public API for programmatic use and CI pipelines:
npm install depwire-cli
import {
parseProject,
buildGraph,
calculateHealthScore,
analyzeDeadCode,
generateDocs,
scanSecurity,
SimulationEngine,
detectCrossLanguageEdges,
searchSymbols,
getImpact,
getArchitectureSummary,
DepwireSDKVersion
} from 'depwire-cli/sdk';
The SDK is the stable public API surface. All integrations should import from depwire-cli/sdk — never from internal paths.
Why Depwire
| Depwire | RAG-based tools | LLM scanning | |
|---|---|---|---|
| Approach | Deterministic graph | Probabilistic match | Brute force |
| Accuracy | 100% — tree-sitter AST | ~70% — embedding match | Varies |
| Refactor safety | Full call chain tracing | Misses indirect refs | Blind edits |
| Token cost | Ultra-low — surgical reads | High — context stuffing | Extreme |
| Cross-language | REST + subprocess edges | None | None |
| Security scanner | Graph-aware severity | None | None |
| What If simulation | Before touching code | None | None |
| Multi-module JVM support | Full cross-module resolution | None | None |
| Runs locally | Always | Varies | Never |
Language support
TypeScript, JavaScript, Python, Go, Rust, C, C#, Java, C++, Kotlin, PHP, Swift, Mojo, Ruby, Dart, R — with cross-language edge detection between all supported languages.
Java / JVM — classes, interfaces, enums, records, annotations, inner classes, anonymous classes, lambda expressions, Maven pom.xml and Gradle build file dependency edges, Spring Boot cross-language edges (@GetMapping, @PostMapping, @RequestMapping), JAX-RS / Jakarta EE route detection, Spring WebFlux RouterFunction support.
C# / .NET — classes, interfaces, records, structs, enums, delegates, file-scoped namespaces, primary constructors, global usings, .csproj ProjectReference and PackageReference edges, ASP.NET Core cross-language edges (attribute routing + Minimal API).
C++ / Systems — classes, structs, unions, enums, namespaces, concepts, coroutines, C++20 modules, template support with parameter stripping. CMakeLists.txt, Conan, and vcpkg dependency edge parsing. Crow, Drogon, Pistache, and cpp-httplib cross-language route detection. Dead code detection with vtable and template exclusions. Health score checks: circular includes, missing header guards, god classes, raw pointer fields, missing virtual destructors. Security scanner: memory safety patterns, format string issues, memory management patterns, process execution safety patterns.
Kotlin / JVM — classes, data classes, sealed classes, objects, companion objects, value classes, type aliases, extension functions, enum classes, annotation classes. Coroutine awareness: suspend functions, GlobalScope detection, structured concurrency checks. build.gradle.kts, build.gradle, and settings.gradle.kts dependency parsing. Spring Boot, Ktor, Http4k, and Ktor Resources cross-language route detection. Android Retrofit outgoing edge detection. Dead code detection with Android lifecycle and Spring annotation exclusions. Security scanner: query safety patterns, credential management patterns, random number generation safety, not-null assertion abuse, Ktor missing auth blocks.
PHP / Web — functions, classes, methods, interfaces, traits, enums, namespaces, use statements, require/include dependency edges. Both procedural and OOP styles. Laravel (Route::get/post/put/delete/patch, middleware), Symfony (#[Route(...)]), Slim Framework, and WordPress REST API (register_rest_route) cross-language route detection. Guzzle and file_get_contents HTTP client edge detection. Dead code detection with WordPress hooks, Laravel service providers, Symfony controllers, and magic method exclusions (__construct, __get, __set, __call). Security scanner: query safety patterns, runtime evaluation safety patterns, process execution safety patterns, regex modifier vulnerabilities, serialization safety patterns, variable handling safety patterns, password hashing safety patterns, deprecated crypto libraries, weak PRNG in security contexts, credential management patterns.
Swift / Apple — functions, methods, initializers (init), deinitializers (deinit), classes, structs, enums, protocols, extensions, actors (Swift concurrency), properties (var, let), computed properties, type aliases, associated types. Package.swift (SPM) dependency parsing. Vapor, Hummingbird, and Perfect cross-language route detection. URLSession and Alamofire HTTP client edge detection. Dead code detection with AppDelegate/SceneDelegate lifecycle, SwiftUI View body, @IBAction/@IBOutlet, @objc, protocol conformance, Codable synthesis, XCTestCase, and @main entry point exclusions. Security scanner: query string safety via string interpolation, Process() execution safety, memory pointer safety patterns, UserDefaults storing sensitive data, CC_MD5/CC_SHA1 weak hashing, Insecure.MD5/SHA1 from CryptoKit, arc4random in crypto contexts, App Transport Security patterns, credential management patterns, hardcoded HTTP URLs.
Mojo / AI-native (strategic support) — fn (typed functions), def (Python-compatible functions), structs (value types), classes, traits (interfaces), alias (type aliases and compile-time constants), var/let declarations, import and from...import statements. Pattern-based parser (no tree-sitter-mojo available). Supports @value, @register_passable, @staticmethod decorators, inout/owned/borrowed parameter modifiers, SIMD/Tensor/DType type references. mojoproject.toml dependency parsing. Python interop detection (from python import). Cross-language route detection via Python framework interop (FastAPI/Starlette). Dead code detection with init/copyinit/moveinit lifecycle, trait implementations, MLIR dialect operations, and @export exclusions. Security scanner: Pointer[T] and DTypePointer memory safety, Python interop evaluation safety, uninitialized memory patterns, SIMD bounds safety, weak random via Python random module, hardcoded keys in alias declarations, hashlib via Python interop in crypto contexts. Mojo is the first AI-native language supported by Depwire.
Ruby / Web — method definitions (def, def self.), classes, modules, instance variables (@var), class variables (@@var), constants, attr_accessor/attr_reader/attr_writer, require/require_relative dependency edges, include/extend/prepend mixin edges, blocks, procs, lambdas, Struct and OpenStruct definitions, ActiveSupport::Concern support. Gemfile dependency parsing. Rails (get/post/put/patch/delete/resources/namespace in routes.rb), Sinatra (route + do blocks), Rack (map/run/use in config.ru), and Grape API cross-language route detection. Faraday, Net::HTTP, and HTTParty HTTP client edge detection. Dead code detection with Rails controller callbacks, ActiveRecord lifecycle callbacks, rake tasks, RSpec/Minitest methods, concerns (included/class_methods blocks), initialize, method_missing/respond_to_missing?, Pundit policy methods, and Devise strategy exclusions. Security scanner: string interpolation in database query methods, command execution safety patterns, runtime evaluation safety patterns, dynamic dispatch safety patterns, file operation safety patterns, YAML deserialization safety, Marshal deserialization safety, template rendering safety patterns, weak hash algorithms (Digest::MD5/SHA1), weak random (rand vs SecureRandom), credential management patterns, SSL verification patterns, weak cipher algorithms.
Dart / Flutter — classes, abstract classes, sealed classes (Dart 3.0+), mixins, extensions, enhanced enums, typedefs, records, top-level functions and variables, constructors (named and factory), methods, getters/setters, fields. import/export/part/part of/library directives with relative path resolution. pubspec.yaml dependency parsing. Flutter widget tree awareness: StatelessWidget, StatefulWidget, State<T> subclass detection, build() method composition tracking. Shelf router, Aqueduct/Conduit, Angel framework, and Serverpod endpoint cross-language route detection. Dio, http package, Chopper (@Get/@Post), and Retrofit Dart (@GET/@POST) HTTP client edge detection. Dead code detection with Flutter widget lifecycle (initState, dispose, build, didChangeDependencies, didUpdateWidget), framework override methods, serialization methods (fromJson/toJson/copyWith), Riverpod providers, Bloc/Cubit event handlers, GetX controller lifecycle, test methods, and mock class exclusions. Security scanner: string interpolation in database queries, process execution safety, runtime reflection patterns, file path safety, JSON decoding validation, WebView JavaScript channel safety, platform channel validation, unencrypted local storage patterns, weak hashing for credentials, insecure random generation, credential management patterns, SSL certificate validation, insecure HTTP connections, and SharedPreferences vs FlutterSecureStorage patterns. Pattern-based parser (no tree-sitter-dart WASM available).
R / Statistics & Data Science — functions (including anonymous functions and closures), S3/S4/R5/R6 class definitions, methods, variable assignments (both <- and = forms), library/require/source dependency edges, NAMESPACE import/export directives, DESCRIPTION file dependency parsing. Pattern-based parser (tree-sitter-r unavailable on npm). Cross-language edge detection: plumber HTTP API route definitions (@get, @post, @put, @delete, @patch decorators) matched to client callers; Shiny reactive graph edges (server/UI function wiring, observe, reactive, eventReactive, renderXxx output bindings); outgoing HTTP client edges via httr (GET, POST, PUT, DELETE) and httr2 (request + req_perform); DBI database connection edges (dbConnect, dbGetQuery, dbExecute); reticulate Python interop edges (import_from_path, source_python, py_run_file). Dead code detection with S3/S4 generic registration exclusions, Shiny module server/UI functions, and testthat/RUnit test block exclusions. Security scanner: string interpolation in database query calls, system/system2/shell execution safety patterns, eval/parse runtime evaluation safety, file path handling safety, credential management patterns, weak PRNG in statistical-security contexts (sample/runif vs openssl for key material), and unvalidated input in plumber route handlers.
GitHub Action — PR Impact Analysis
Depwire integrates into your CI/CD pipeline via the depwire-action GitHub Action.
On every pull request it automatically posts a dependency impact report — which symbols changed, what breaks, health score before and after. Code reviewers see the architectural blast radius before merging.
Add to .github/workflows/depwire.yml:
name: Depwire PR Impact
on:
pull_request:
branches: [main]
permissions:
contents: read
pull-requests: write
jobs:
depwire:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- uses: actions/setup-node@v4
with:
node-version: '20'
- uses: depwire/depwire-action@v1
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
Block PRs that hurt your architecture:
- uses: depwire/depwire-action@v1
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
fail-on-score-drop: 5
GitHub Marketplace — depwire-action repo
Cloud dashboard
app.depwire.dev — full dependency graph, health score, dead code report, and AI codebase chat in the browser. No local setup required.
- Free for public repos
- Pro ($19/month) — unlimited repos, private repo support, AI codebase chat
Roadmap
Shipped
- Arc diagram visualization
- 23 MCP tools
- Multi-language support (TypeScript, JavaScript, Python, Go, Rust, C, C#, Java, C++, Kotlin, PHP, Swift, Mojo, Ruby, Dart, R)
- Architecture health score
- Dead code detection
- Temporal graph
- What If simulation — CLI + browser UI
- Security scanner — graph-aware severity elevation
- Cross-language edge detection — REST API + subprocess
- Structural diff between commits —
depwire diff - Public SDK —
depwire-cli/sdk - Cloud dashboard — app.depwire.dev
- PR Impact GitHub Action
Coming next
- AI-suggested refactors
- VSCode extension
- Natural language architecture queries
Security posture
Depwire is read-only. It never writes to, modifies, or executes your code.
- Parses with tree-sitter — the same parser used by VS Code and Zed
- Visualization server binds to localhost only
- No data leaves your machine
- Blocks access to sensitive system directories
- npm packages published with provenance verification
See SECURITY.md for full details.
Contributing
- Fork the repository
- Create a feature branch
- Add tests for new functionality
- Submit a pull request
- Sign the CLA (handled automatically on your first PR)
Author
Atef Ataya — AI architect, author, and creator of Depwire.
- YouTube — 600K+ subscribers covering AI agents, MCP, and LLMs
- The Architect's Playbook: 5 Pillars
Depwire Action Token (DAT)
Depwire is the reference implementation of the Depwire Action Token (DAT) — an open standard for cryptographically signing AI agent actions. DAT provides tamper-proof audit trails for every tool call, file change, and agent delegation.
License
Business Source License 1.1 — free for personal and internal company use. Converts to Apache 2.0 on February 25, 2029.
Commercial licensing: atef@depwire.dev
Built with tree-sitter, graphology, D3.js, and the Model Context Protocol.
常见问题
io.github.atef-ataya/depwire 是什么?
提供依赖图和 10 个面向 AI 编码的 MCP 工具,支持 TypeScript、Python、JS 与 Go。
相关 Skills
前端设计
by anthropics
面向组件、页面、海报和 Web 应用开发,按鲜明视觉方向生成可直接落地的前端代码与高质感 UI,适合做 landing page、Dashboard 或美化现有界面,避开千篇一律的 AI 审美。
✎ 想把页面做得既能上线又有设计感,就用前端设计:组件到整站都能产出,难得的是能避开千篇一律的 AI 味。
网页应用测试
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用 Playwright 为本地 Web 应用编写自动化测试,支持启动开发服务器、校验前端交互、排查 UI 异常、抓取截图与浏览器日志,适合调试动态页面和回归验证。
✎ 借助 Playwright 一站式验证本地 Web 应用前端功能,调 UI 时还能同步查看日志和截图,定位问题更快。
网页构建器
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面向复杂 claude.ai HTML artifact 开发,快速初始化 React + Tailwind CSS + shadcn/ui 项目并打包为单文件 HTML,适合需要状态管理、路由或多组件交互的页面。
✎ 在 claude.ai 里做复杂网页 Artifact 很省心,多组件、状态和路由都能顺手搭起来,React、Tailwind 与 shadcn/ui 组合效率高、成品也更精致。
相关 MCP Server
GitHub
编辑精选by GitHub
GitHub 是 MCP 官方参考服务器,让 Claude 直接读写你的代码仓库和 Issues。
✎ 这个参考服务器解决了开发者想让 AI 安全访问 GitHub 数据的问题,适合需要自动化代码审查或 Issue 管理的团队。但注意它只是参考实现,生产环境得自己加固安全。
Context7 文档查询
编辑精选by Context7
Context7 是实时拉取最新文档和代码示例的智能助手,让你告别过时资料。
✎ 它能解决开发者查找文档时信息滞后的问题,特别适合快速上手新库或跟进更新。不过,依赖外部源可能导致偶尔的数据延迟,建议结合官方文档使用。
by tldraw
tldraw 是让 AI 助手直接在无限画布上绘图和协作的 MCP 服务器。
✎ 这解决了 AI 只能输出文本、无法视觉化协作的痛点——想象让 Claude 帮你画流程图或白板讨论。最适合需要快速原型设计或头脑风暴的开发者。不过,目前它只是个基础连接器,你得自己搭建画布应用才能发挥全部潜力。