# AI Code Reviewer - Analyze, Explain & Improve Code (`ntriqpro/code-review-intelligence-mcp`) Actor Get AI-powered feedback on code quality, security issues, and improvement suggestions. Explain complex code in plain English. - **URL**: https://apify.com/ntriqpro/code-review-intelligence-mcp.md - **Developed by:** [daehwan kim](https://apify.com/ntriqpro) (community) - **Categories:** MCP servers, AI, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event + usage This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Code Review Intelligence MCP Server Review, explain, and generate code using local AI. No code is sent to external APIs — 100% privacy. ### Features | Tool | Description | Price | |------|-------------|-------| | `review_code` | Review code for bugs, security, performance, or readability issues | $0.10/use | | `explain_code` | Explain code with adjustable detail (brief, medium, detailed) | $0.05/use | | `generate_code` | Generate new code or refactor existing code from instructions | $0.10/use | ### Connect via Claude Desktop Add to your Claude Desktop MCP settings: ```json { "mcpServers": { "code-review": { "url": "https://ntriqpro--code-review-intelligence-mcp.apify.actor/mcp?token=YOUR_APIFY_TOKEN" } } } ```` ### Review Focus Areas | Focus | Description | |-------|-------------| | `general` | Bugs, improvements, best practices (default) | | `security` | Vulnerabilities: injection, XSS, auth issues, data exposure | | `performance` | Bottlenecks, unnecessary operations, optimizations | | `readability` | Naming, structure, documentation, maintainability | ### Supported Languages All major programming languages: Python, JavaScript, TypeScript, Go, Rust, Java, C++, Ruby, PHP, Swift, Kotlin, and more. ### Input #### review\_code - `code` (required): Source code to review - `language` (optional): Programming language (default: auto-detect) - `focus` (optional): "general", "security", "performance", "readability" #### explain\_code - `code` (required): Source code to explain - `detailLevel` (optional): "brief", "medium", "detailed" #### generate\_code - `instruction` (required): What to build or how to refactor - `existingCode` (optional): Existing code to refactor - `language` (optional): Target language (default: "python") ### Output Examples #### review\_code (security focus) ```json { "status": "success", "review": "**Security Review**\n\n1. **Critical**: SQL injection vulnerability on line 15...\n2. **High**: Hardcoded API key on line 3...", "focus": "security", "model": "qwen2.5-coder" } ``` #### explain\_code (brief) ```json { "status": "success", "explanation": "This is a REST API endpoint that handles user authentication using JWT tokens and bcrypt password hashing.", "detail_level": "brief", "model": "qwen2.5-coder" } ``` ### Technology - **Code Model**: Qwen2.5-Coder 7B (Apache 2.0 License) - **Processing**: Local AI inference, zero external API calls - **Privacy**: Code is processed in real-time and not stored ### Open Source Licenses This service uses the following open source model: - [Qwen2.5-Coder](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) — Apache 2.0 License ### Legal Disclaimer **Code Review Notice**: This service provides AI-generated code analysis suggestions only. All outputs are recommendations and should not be treated as automated decisions. Human review and verification is required before acting on any suggestions. This service does not guarantee the detection of all bugs, vulnerabilities, or issues. Code submitted for analysis is processed in real-time, is not stored, and is not used for model training. This service does not constitute professional software auditing or security certification. Platform usage is free. You only pay per event (see pricing above). *** ### 🔗 Related Actors by ntriqpro Extend this actor with the ntriqpro intelligence network: - [**supply-chain-risk-mcp**](https://apify.com/ntriqpro/supply-chain-risk-mcp) — MCP server for supply chain risk - [**video-intelligence-mcp**](https://apify.com/ntriqpro/video-intelligence-mcp) — MCP server for video intelligence - [**content-factory-mcp**](https://apify.com/ntriqpro/content-factory-mcp) — MCP server for content-factory ### ⭐ Love it? Leave a Review Your rating helps professionals discover this actor. [Rate it here](https://apify.com/ntriqpro/code-review-intelligence-mcp/reviews). # Actor input Schema ## `standbyTimeout` (type: `integer`): How long (in seconds) the MCP server stays active waiting for tool calls before shutting down. Default is 300 seconds (5 minutes). Increase for long-running sessions. ## `logLevel` (type: `string`): Controls how much detail appears in the Actor log. Use 'info' for normal operation, 'debug' for troubleshooting, or 'error' for minimal output. ## Actor input object example ```json { "standbyTimeout": 300, "logLevel": "info" } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "standbyTimeout": 300, "logLevel": "info" }; // Run the Actor and wait for it to finish const run = await client.actor("ntriqpro/code-review-intelligence-mcp").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "standbyTimeout": 300, "logLevel": "info", } # Run the Actor and wait for it to finish run = client.actor("ntriqpro/code-review-intelligence-mcp").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "standbyTimeout": 300, "logLevel": "info" }' | apify call ntriqpro/code-review-intelligence-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ntriqpro/code-review-intelligence-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Code Reviewer - Analyze, Explain & Improve Code", "description": "Get AI-powered feedback on code quality, security issues, and improvement suggestions. Explain complex code in plain English.", "version": "1.0", "x-build-id": "MF9KPbm1aDhz8Xftq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ntriqpro~code-review-intelligence-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ntriqpro-code-review-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ntriqpro~code-review-intelligence-mcp/runs": { "post": { "operationId": "runs-sync-ntriqpro-code-review-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ntriqpro~code-review-intelligence-mcp/run-sync": { "post": { "operationId": "run-sync-ntriqpro-code-review-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "standbyTimeout": { "title": "Standby Timeout (seconds)", "minimum": 60, "maximum": 3600, "type": "integer", "description": "How long (in seconds) the MCP server stays active waiting for tool calls before shutting down. Default is 300 seconds (5 minutes). Increase for long-running sessions." }, "logLevel": { "title": "Log Level", "enum": [ "info", "debug", "error" ], "type": "string", "description": "Controls how much detail appears in the Actor log. Use 'info' for normal operation, 'debug' for troubleshooting, or 'error' for minimal output." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```