Lenspr

Name: Lenspr
Author: kyrylopr

by kyryloprversion 0.1.1i★ –iRuns on your computer

Registry nameio.github.kyrylopr/lenspr

Install

Overview

Description from the maker (original English)

Stop vibecoding blind. Code graph so your AI stops breaking things across your codebase.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 13/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "lenspr": {
      "command": "uvx",
      "args": [
        "lenspr"
      ]
    }
  }
}

Run this in your terminal

claude mcp add lenspr -- uvx lenspr

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "lenspr": {
      "command": "uvx",
      "args": [
        "lenspr"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "lenspr": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "lenspr"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account kyrylopr, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

More stars than 0% of the other 5547 servers in this category
Published to the registry more recently than 4% of the other 5547 servers in this category
Basic checks equal to or better than 100% of the other 5547 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Lenspr safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 9 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

GitHub

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

by githubWidely used★ 34.2KUpdated 5 days ago

Computer or cloud

Install

Desktop Commander

MCP server for terminal commands, file operations, and process management

by wonderwhy-erWidely used↓ 709.6K/wk★ 10.2KUpdated 17 days ago

Runs on your computer

Install

Cloudflare MCP

Cloudflare MCP servers

by cloudflareWidely used★ 4.4KUpdated 14 months ago

Runs in the cloud✓ mcp.cloudflare.com

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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.

Quick Start

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.

What It Does

"What depends on this function?"

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.

"What breaks if I change this?"

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.

"How healthy is this codebase?"

> 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.

Cross-language visibility

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.

Works With

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.

Key Features


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

Known Limitations

Windows — not supported. macOS and Linux only.
`self.method()` calls — static parser can't fully resolve instance method dispatch. Workaround: lens_trace (Python 3.12+) resolves these at runtime.
Go, Rust, Java — not yet supported. Parser interface is ready for contributors.
Dynamic code — getattr, eval, dynamic imports can't be tracked statically.

Contributing

Try it. If it breaks, tell me.

Bug reports — even "this doesn't work" is helpful
Language parsers — Go, Rust, Java (BaseParser interface is ready)
Ideas — open an issue

License

MIT

Built because AI kept breaking my code.

Lenspr

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Developer toolsi

Common questions

Alternatives

GitHub

Desktop Commander

Cloudflare MCP

README from the maker

Quick Start

What It Does

"What depends on this function?"

"What breaks if I change this?"

"How healthy is this codebase?"

Cross-language visibility

Works With

Key Features

Known Limitations

Contributing

License