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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.


Related MCP server: codemap

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 <path>

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.

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 codegetattr, 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)

  • Ideasopen an issue

License

MIT


Built because AI kept breaking my code.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

No tool schema history has been recorded yet.

Maintenance

ActivityInactive
ResponsivenessNo issues

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