GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Stop vibecoding blind. Code graph so your AI stops breaking things across your codebase.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"lenspr": {
"command": "uvx",
"args": [
"lenspr"
]
}
}
}在终端中运行这条命令
claude mcp add lenspr -- uvx lenspr粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"lenspr": {
"command": "uvx",
"args": [
"lenspr"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"lenspr": {
"type": "stdio",
"command": "uvx",
"args": [
"lenspr"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 kyrylopr 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.1)于9个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Code intelligence for AI coding agents. Your AI sees dependencies before making changes.
Alpha (0.1.x) — works on real projects, used daily by the author. Expect rough edges.
AI assistants edit your code one file at a time. They don't see dependencies. They grep, read, guess — and break things three files away.
LensPR builds a dependency graph of your codebase and gives your AI structural understanding before it changes anything.
Requires Python 3.11+, macOS or Linux. For TypeScript/JS projects, also Node.js 18+.
pip install 'lenspr[all]'
lenspr init . lenspr setup .
Restart your IDE. Done. Your AI now has lens_* tools.
Add
.lens/to your.gitignore— the graph is local and rebuilt from source.
One call returns source code, who calls it, what it calls, and related tests:
> lens_context("auth.login_handler")
source: 42 lines callers: auth_routes.create_routes, test_auth.test_login_success callees: db.get_user, crypto.verify_password, jwt.create_token tests: test_login_success, test_login_wrong_password
Without LensPR your AI makes 5-7 grep/read calls and still misses things. With LensPR — one call, full picture.
Before any modification, the AI sees the blast radius:
> lens_check_impact("models.User")
severity: CRITICAL direct_dependents: 15 indirect_dependents: 23 affected_modules: auth, payments, notifications tests_covering: 3
The AI warns you, changes its approach, or asks for confirmation. No more blind edits.
> lens_vibecheck()
score: 86/100 (B) test_coverage: 17/25 — 67% functions tested dead_code: 20/20 — 0% dead code circular_imports: 15/15 — 0 cycles architecture: 12/15 — 1 violation documentation: 8/10 — 81% documented graph_confidence: 14/15 — 94% edges resolved
Track whether the codebase is improving or degrading over time.
LensPR connects frontend and backend into a single graph:
LoginModal.tsx → fetch("/api/auth/login")
↓ CALLS_API Backend: @router.post("/login") → login_handler() → db.query(User) [reads: users] → verify_password() → create_jwt_token()
Also tracks: database tables, Docker services, env vars, CI/CD workflows, SQL migrations.
| IDE | Setup |
|---|---|
| Claude Code | lenspr setup . — automatic |
| Cursor | Copy .mcp.json to .cursor/mcp.json |
| Any MCP client | lenspr serve |
Languages: Python (95%+ resolution via Jedi/Pyright) and TypeScript/JavaScript (85-95% via tree-sitter + TS Compiler API).
Infrastructure: .sql files, Dockerfiles, docker-compose.yml, GitHub Actions workflows, .env files — all parsed into the same graph.
Everything runs locally. Your code never leaves your machine.
| Impact Analysis | Severity (LOW → CRITICAL) before any change |
| One-Call Context | Source + callers + callees + tests in one request |
| Cross-Language | Frontend HTTP → backend routes, DB tables, Docker, env vars, CI/CD |
| Surgical Edits | Targeted find/replace within a function — no full file rewrites |
| Dead Code | Find unreachable functions (Django, FastAPI, Celery entry points) |
| Architecture Rules | Enforce layer boundaries — violations warn before changes apply |
| Git per Function | Blame, history, commit scope at function level |
| Session Memory | AI picks up where it left off across context resets |
| Auto-Sync | File watcher updates graph on every save |
| Health Score | 0-100 score across 6 dimensions — track quality over time |
60+ tools organized in 12 groups — enable only what you need with lenspr tools.
All tools by category
Navigation & Search (8): lens_context, lens_get_node, lens_search, lens_grep, lens_find_usages, lens_get_structure, lens_list_nodes, lens_get_connections
Modification (6): lens_update_node, lens_patch_node, lens_add_node, lens_delete_node, lens_rename, lens_batch
Analysis (6): lens_check_impact, lens_validate_change, lens_health, lens_dead_code, lens_dependencies, lens_diff
Quality (7): lens_vibecheck, lens_nfr_check, lens_test_coverage, lens_security_scan, lens_dep_audit, lens_fix_plan, lens_generate_test_skeleton
Architecture (9): lens_arch_rule_add, lens_arch_rule_list, lens_arch_rule_delete, lens_arch_check, lens_class_metrics, lens_project_metrics, lens_largest_classes, lens_compare_classes, lens_components
Git (4): lens_blame, lens_node_history, lens_commit_scope, lens_recent_changes
Infrastructure (5): lens_api_map, lens_db_map, lens_env_map, lens_ffi_map, lens_infra_map
Testing & Tracing (3): lens_run_tests, lens_trace, lens_trace_stats
Annotations (5): lens_annotate, lens_save_annotation, lens_batch_save_annotations, lens_annotate_batch, lens_annotation_stats
Session (4): lens_session_write, lens_session_read, lens_session_handoff, lens_resume
Temporal (2): lens_hotspots, lens_node_timeline
Explanation (1): lens_explain
lens_trace (Python 3.12+) resolves these at runtime.getattr, eval, dynamic imports can't be tracked statically.Try it. If it breaks, tell me.
MIT
Built because AI kept breaking my code.