ReviewLens MCP Server

ReviewLens MCP Server

Enables secure, explainable AI-assisted GitHub pull-request review by exposing seven read-only tools that collect deterministic evidence from PRs, separating retrieval from interpretation.

Category
Visit Server

README

ReviewLens MCP

A secure, explainable MCP server for AI-assisted GitHub pull-request review.

ReviewLens exposes seven typed, read-only tools that collect evidence from pull requests. It separates deterministic evidence collection from model interpretation, treats repository content as untrusted data, and includes a credential-free simulated provider and web demo.

ReviewLens MCP product walkthrough

Why it exists

AI review assistants often collapse retrieval, interpretation, and action into one opaque step. ReviewLens keeps those concerns separate so tool calls are auditable, contracts are testable, and no model can mutate a repository through this server.

Product tour

The deterministic demo completes a realistic pull-request review without requiring a GitHub token. It exposes the collected evidence, related tests, risk level, and any instruction-like content found in untrusted repository data.

Simulated pull-request review with structured evidence

The tool surface is intentionally small: seven operations with explicit inputs and one responsibility each. The architecture keeps MCP at the adapter boundary and isolates review logic from GitHub access.

ReviewLens tools and architecture

The security model is visible rather than implied: least privilege, bounded evidence, untrusted-content handling, and explicit failures. A restrained pixel-art signature connects the project to its creator without competing with the engineering content.

ReviewLens security model and creator signature

Quick start — demo mode

python -m venv .venv
# Windows: .venv\Scripts\activate
# macOS/Linux: source .venv/bin/activate
python -m pip install -e ".[dev]"
pytest
reviewlens-demo

Open http://127.0.0.1:8000. The demo always uses deterministic fixture data.

Run the MCP server

reviewlens-mcp

The default transport is stdio.

Tools

Tool Purpose
list_pull_requests List open pull requests
get_pull_request Fetch PR metadata
get_pull_request_files Collect changed files and patches
get_pull_request_diff Return a bounded, redacted diff
search_repository_code Search repository code
find_related_tests Locate tests connected to changed paths
build_review_report Assemble deterministic structured evidence

Live mode

Copy .env.example to .env, set REVIEWLENS_MODE=live, and optionally configure a fine-grained token or GitHub App installation token with read-only Contents and Pull requests permissions. Tokens remain server-side.

Architecture and security

See docs/architecture.md, docs/security.md, and docs/adr/. The MVP contains no write-capable provider method, MCP tool, or demo endpoint.

Verification

ruff check .
mypy src
pytest

Documentation

  • Spanish: README.es.md
  • Recording guide: docs/demo-recording.md
  • Limitations: docs/limitations.md

Author

Built by Paula García Fernández.

Copyright

Copyright © 2026 Paula García Fernández. All rights reserved. The repository is viewable as a personal portfolio and technical demonstration; reuse requires prior written permission. See COPYRIGHT.md. Audio is intentionally absent from v1.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured