Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

Frontend Perception Engine (CRG as Optional Library)

This project implements a frontend navigation layer where:

  • Browser Use stays the browser automation engine.
  • Code Review Graph (CRG) is used only as an optional knowledge source.
  • Browser execution continues even when CRG is unavailable.

Architecture

Cursor / Claude
   ↓
Our MCP
   ↓
Frontend Navigation Layer
   ↓
Browser Use
   ↓
Browser

CRG is integrated behind ICodeGraph, so it can be replaced later by another backend such as FrontendInteractionGraph without changing Browser Use orchestration.

Dependency Integration

CRG is integrated as a dependency (not forked, not modified):

  • code-review-graph>=2.3.6
  • browser-use>=0.13.3

Install:

pip install -e .

Frontend Perception MCP (No LLM in Server)

The MCP server is deterministic runtime only (browser observation + actions + verify).
Your coding agent (Cursor/Claude/Codex) remains the brain.

Install

Both PyPI names install the same MCP server:

Package Install / upgrade
frontend-perception-engine pip install --upgrade frontend-perception-engine
frontend-mcp (alias) pip install --upgrade frontend-mcp

Use --upgrade when a version is already installed — plain pip install may leave an older release in place.

Do not mix PyPI installs with pip install -e . in this repo; editable installs can leave broken metadata that blocks upgrades. Use one or the other.

Recommended (quiet output + next steps):

uvx --from frontend-perception-engine frontend-perception-install

Or the shorter alias name:

uvx --from frontend-mcp frontend-mcp-install

With Chromium for Browser Use:

uvx --from frontend-perception-engine frontend-perception-install --with-browser

Development install from this repo:

python -m navigation.cli.install --editable .

Or classic pip:

pip install frontend-perception-engine

Run MCP server

Using module entrypoint:

python -m navigation.mcp

Using script entrypoint:

frontend-perception-mcp

Using uvx (no local install in current environment):

uvx --from frontend-perception-engine frontend-perception-mcp
# or
uvx --from frontend-mcp frontend-mcp

Cursor MCP config

{
  "mcpServers": {
    "frontend-perception": {
      "command": "python",
      "args": ["-m", "navigation.mcp"],
      "env": {
        "PYTHONPATH": "C:/Users/usman/Projects/frontend-perception-engine/src"
      }
    }
  }
}

Runtime prerequisites

  • Start the sandbox app: cd sandbox && npm run dev
  • Default URL used by tests/tools: http://localhost:5173
  • No API keys are required to run the MCP path itself

Platform documentation

Architecture, roadmap, tool reference, and feature subsystem docs: docs/README.md.

CRG Documentation and Public API Notes

The integration uses CRG public tool functions from:

  • code_review_graph.tools.build.build_or_update_graph
  • code_review_graph.tools.query.query_graph
  • code_review_graph.tools.query.semantic_search_nodes
  • code_review_graph.tools.query.get_impact_radius
  • code_review_graph.tools.query.list_graph_stats
  • code_review_graph.tools.query.traverse_graph_func

Graph lifecycle

  • Initialize graph (incremental/minimal): build_or_update_graph(full_rebuild=False, postprocess="minimal")
  • Refresh graph (incremental): build_or_update_graph(full_rebuild=False)
  • Rebuild graph (full): build_or_update_graph(full_rebuild=True)

Incremental indexing

CRG incremental path is handled by incremental_update under the hood and can detect changed files from VCS (base=HEAD~1 by default).

Watch mode

CRG supports continuous updates via:

  • CLI: code-review-graph watch
  • API internals: code_review_graph.incremental.watch and start_watch_thread

This wrapper does not require watch mode, but is compatible with repositories kept fresh by CRG watch/daemon.

Querying

  • Pattern queries (neighbors/file relationships): query_graph
  • Search (hybrid semantic + keyword): semantic_search_nodes
  • Blast radius / route impact: get_impact_radius
  • Traversal/path-like exploration: traverse_graph_func
  • Stats/health: list_graph_stats

Wrapper Layer

All CRG coupling is isolated in:

src/navigation/codeGraph/

Public contract:

  • initialize()
  • refresh()
  • rebuild()
  • search()
  • shortest_path()
  • get_neighbors()
  • get_component()
  • get_file()
  • get_route()
  • query()

Future-oriented methods are already represented on ICodeGraph:

  • findNavigationHint(...) style equivalent via find_navigation_hint(...)
  • find_relevant_components(...)
  • find_likely_route(...)
  • find_related_files(...)
  • find_button_candidates(...)
  • find_component_hierarchy(...)
  • find_entry_point(...)

Browser Use Integration

BrowserUseNavigator provides a lightweight dry-run timeline for tests.

PerceptionAgentRunner runs a real Browser Use agent with optional graph hints injected via extend_system_message. Graph output is never a mandatory stage — if CRG or AWS credentials are missing, the agent either skips hints or reports a clear error.

Live agent (Bedrock Nova)

  1. Start the sandbox:
cd sandbox && npm run dev
  1. Configure AWS (copy .env.example.env):
AWS_ACCESS_KEY_ID=...
AWS_SECRET_ACCESS_KEY=...
AWS_REGION=us-east-1
BEDROCK_MODEL=amazon.nova-pro-v1:0
SANDBOX_URL=http://localhost:5173
  1. Install AWS extra and run:
pip install -e ".[aws]"
python src/run_agent.py --task "Add Pulse Watch to cart and complete checkout"

Dry-run (graph hints only, no browser):

python src/run_agent.py --dry-run --task "Log in as admin and open admin report"

Flags:

  • --no-graph — disable CRG hints
  • --headless — headless browser
  • --max-steps 25 — step limit
  • --url http://localhost:5174 — custom sandbox URL

Demo

Run:

python src/demo.py

Expected behavior:

  1. Browser Use execution starts.
  2. Optional code graph query is attempted.
  3. Browser Use continues regardless of query success.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

frontend_perception_engine-1.2.0.dev19.tar.gz (1.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file frontend_perception_engine-1.2.0.dev19.tar.gz.

File metadata

File hashes

Hashes for frontend_perception_engine-1.2.0.dev19.tar.gz
Algorithm Hash digest
SHA256 7bdd7de0484f87ac60fe5478e4923eab8880eb91852c112c759d7e17c9c47198
MD5 03e0f8bf1b6820f221505ad19afe4cfc
BLAKE2b-256 daba8e9fe673e1587418fef3bd641565e998ae0c463345a03628f637f7bf7682

See more details on using hashes here.

File details

Details for the file frontend_perception_engine-1.2.0.dev19-py3-none-any.whl.

File metadata

File hashes

Hashes for frontend_perception_engine-1.2.0.dev19-py3-none-any.whl
Algorithm Hash digest
SHA256 e830f10320dde6ff71540dd17ffadbafd0952a1ab22cb9a633bf5f455cf1aa34
MD5 18dd1eb10e1f294760b076eb7b638c4f
BLAKE2b-256 864c562c502af29af07800b1dab6152f41f073d59f3276205e5c09f3b8048de7

See more details on using hashes here.

Release history Release notifications | RSS feed

1.2.0

2 files

This release

1.2.0.dev19 This release

2 files

1.1.7

2 files

1.1.6

2 files

1.1.5

2 files

1.1.4

2 files

1.1.3

2 files

1.1.2

2 files

1.1.1

2 files

1.1.0

2 files

1.0.1

2 files

1.0.0

2 files

0.2.0

2 files

0.1.2

2 files

0.1.1

2 files

0.1.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page