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Vetted Servers(8554)

0
0
Medium Cost
maxamillion icon

rhoai-mcp-prototype

by maxamillion

Sec8

Enables AI agents to programmatically interact with Red Hat OpenShift AI (RHOAI) environments, replicating dashboard capabilities for ML lifecycle management.

Setup Requirements

  • ⚠️Requires access to a Red Hat OpenShift AI Kubernetes cluster.
  • ⚠️Proper Kubernetes authentication (in-cluster service account, kubeconfig file, or API server URL and token) must be configured.
  • ⚠️Requires Python 3.10 or newer.
Verified SafeView Analysis
The server directly interacts with the Kubernetes API. Its security depends on the permissions of the Kubernetes service account or kubeconfig it uses. It includes safety features like explicit confirmation for 'delete' operations and a 'read-only' mode, which are good practices. No 'eval' or obvious obfuscation detected. Hardcoded secrets are not present; S3 credentials for data connections are passed to tools and stored as Kubernetes secrets. The primary risk is granting the server (and thus, an AI agent interacting with it) excessive permissions to the underlying OpenShift AI cluster.
Updated: 2026-01-19GitHub→
0
0
Low Cost
BradWebb101 icon

mcp-as-a-resume

by BradWebb101

Sec4

Transforms a static resume into a living, queryable API using the Model Context Protocol (MCP) for AI agents and applications, enabling programmatic access to professional information.

Setup Requirements

  • ⚠️Requires AWS Account with configured credentials, Node.js, npm, Docker, and AWS CDK CLI.
  • ⚠️The provided CDK stack only deploys the Lambda and DynamoDB. CloudFront and Route53 (mentioned in the README as part of the architecture) are not provisioned by this stack, requiring manual setup or an external CDK stack to utilize a custom domain and add a security layer.
  • ⚠️Amazon SES sender and recipient emails must be verified in the AWS region specified (eu-west-1 in the provided code) before emails can be sent.
Verified SafeView Analysis
The Lambda Function URL is configured with 'NONE' authentication, directly exposing the Lambda endpoint to the public internet without inherent AWS IAM protection. While the README mentions CloudFront for HTTPS and global distribution, the provided AWS CDK code (`lib/resume-mcp-stack.ts`) does not provision a CloudFront distribution, implying it must be manually configured or handled by an external stack to add essential security layers (e.g., WAF, rate limiting, DDoS protection) in front of the Lambda. There is no explicit input validation (e.g., length, format) for parameters like `sender_email` or `message` in the `send_email_to_brad` function, which could lead to abuse (e.g., very large messages or malformed emails). Error responses return `str(e)`, which may leak sensitive stack trace information in case of unhandled exceptions.
Updated: 2025-11-23GitHub→
0
0
Medium Cost
onoeserika007 icon

Local-Notes-MCP-Server

by onoeserika007

Sec6

An AI-powered personal knowledge base and note management system with Obsidian integration, supporting full-text and semantic search.

Setup Requirements

  • ⚠️Requires a Tongyi Qianwen (Qwen) API Key for AI features (paid service).
  • ⚠️Requires Python 3.11+ and Node.js 18+.
  • ⚠️Frontend uses pnpm for package management, not npm.
  • ⚠️Obsidian integration requires `OBSIDIAN_VAULT_PATH` environment variable to be configured for file syncing and display.
Verified SafeView Analysis
The default `SECRET_KEY` in `backend/app/core/config.py` is a placeholder and poses a significant security risk if not changed in production. The system relies on a Qwen API Key for AI features, which must be secured. CORS settings are appropriate for local development but need careful review for production. SQL injection is mitigated by SQLAlchemy, and path traversal is handled using `pathlib` for Obsidian integration. Markdown rendering on the frontend relies on `ReactMarkdown`, which generally sanitizes against XSS, but custom rendering could introduce risks.
Updated: 2025-12-14GitHub→
0
0
Medium Cost
nobiehl icon

codeweaver-mcp

by nobiehl

Sec6

A multi-language code intelligence system providing token-efficient analysis and refactoring capabilities via an MCP server and CLI, with features like semantic search, static analysis, symbol extraction, and Git integration.

Setup Requirements

  • ⚠️Requires Node.js 20.0.0+.
  • ⚠️Semantic search downloads a ~90MB AI embedding model on first use.
  • ⚠️Python analysis features require Python 3.8+ to be installed locally.
  • ⚠️Static analysis tools (SpotBugs, Checkstyle) require their respective command-line tools or Gradle/Maven plugins to be installed and configured locally.
Verified SafeView Analysis
The server executes external commands (e.g., Git, Gradle, Checkstyle, SpotBugs) using `execSync` and `spawnSync`. While some user-provided inputs like file paths and branch names are quoted to prevent basic command injection, there's a potential risk if configuration files for static analysis tools are provided by an untrusted source, as these tools might allow arbitrary code execution through their configurations. Always ensure inputs to external command execution are thoroughly validated and sanitized, especially for `configFile` options.
Updated: 2025-11-25GitHub→
0
0
Low Cost
bhakti259 icon
Sec9

This server allows users to track and manage personal expenses through natural language interactions, storing records in a local SQLite database and providing tools for adding, listing, updating, deleting, and summarizing expenses.

Setup Requirements

  • ⚠️Requires Claude Desktop for primary interaction
  • ⚠️Python 3.12 or higher (as per pyproject.toml)
  • ⚠️Installation may require absolute paths in Claude Desktop config
Verified SafeView Analysis
The server uses parameterized SQLite queries, effectively preventing SQL injection. File paths for the database and categories are local and relative to the script, limiting arbitrary file access. There are no indications of 'eval', obfuscation, hardcoded secrets, or direct external network risks within the provided source code. The date parsing is handled by `python-dateutil`, which is generally robust. The primary risk would be potential data loss or corruption if the local `expenses.db` file is manually tampered with or accidentally deleted.
Updated: 2025-11-27GitHub→
0
0
Low Cost
BlockRunAI icon

awesome-finance-mcp

by BlockRunAI

Sec9

This repository serves as a curated directory of Model Context Protocol (MCP) servers and AI skills relevant to finance, trading, and cryptocurrency agents.

Verified SafeView Analysis
This repository itself is a static collection of Markdown files listing other MCP servers and AI skills; it is not an executable server. Therefore, common code-based security risks like 'eval', obfuscation, or hardcoded secrets are not applicable to this repository directly. The CONTRIBUTING.md outlines quality guidelines for submissions, aiming to ensure listed MCPs are functional and safe, but users should still exercise caution when interacting with external servers linked in the list.
Updated: 2026-01-18GitHub→
0
0
Low Cost
aphoticshaman icon

securescan

by aphoticshaman

Sec8

AI-powered security vulnerability scanner for static code analysis and dependency scanning.

Setup Requirements

  • ⚠️The 'AI-powered' claim is not directly supported by the provided Python scanning logic, which uses regex patterns.
  • ⚠️Conflicting product descriptions and pricing models are present between `README.md` (web-based static site with Stripe payment) and `app.py` (CLI tool with SaaS pricing tiers).
Verified SafeView Analysis
The `app.py` script is a local CLI tool designed to detect vulnerabilities in user-provided code using regex patterns; it does not expose a network interface for its scanning logic. The `serve.py` runs a basic static file server on localhost to host the web interface. Neither component introduces significant server-side security risks. The `eval` patterns and hardcoded secrets identified in the `SAMPLE_CODE` are vulnerabilities that the scanner *detects*, not issues within the scanner's own execution. The 'AI-powered' claim is not demonstrably supported by the provided `app.py` code, which relies on regex for detection.
Updated: 2026-01-19GitHub→
0
0
Low Cost
offerland-cc icon
Sec7

Deploys an unauthenticated Model Context Protocol (MCP) server on Cloudflare Workers, primarily demonstrating calculator tools for AI agents and LLM clients.

Setup Requirements

  • ⚠️Requires a Cloudflare Workers environment for deployment and local development using Wrangler.
  • ⚠️No authentication is configured for the MCP server endpoints (`/sse`, `/mcp`), making it publicly accessible.
Verified SafeView Analysis
The server is explicitly designed as 'authless', meaning it performs no authentication for incoming requests. While this is intentional for its demo purpose (simple calculator tools), it would be a critical security vulnerability if deployed in a production environment handling sensitive data or operations. The code itself does not contain obvious malicious patterns, hardcoded secrets, or `eval` calls.
Updated: 2025-12-05GitHub→
0
0
Medium Cost
dmitry-melnishin icon

mcp-client-and-server

by dmitry-melnishin

Sec8

An MCP server that provides AI-agent callable tools and resources for managing guitar product inventory and customer orders, integrated with a product catalog and fulfillment API.

Setup Requirements

  • ⚠️Requires multiple services (products-api, fulfillment-api, mcp-order-server, frontend, admin) to be run concurrently for full functionality.
  • ⚠️Services use specific local ports: products-api (8082), fulfillment-api (8080), mcp-order-server (9533), admin (3001), frontend (5173). Ensure these ports are available.
  • ⚠️Uses 'pnpm' as the package manager; 'npm' or 'yarn' are not directly supported.
  • ⚠️The 'kill:port' scripts are Windows PowerShell specific.
Verified SafeView Analysis
The system uses Express.js and makes HTTP requests between local services. CORS is configured with `origin: '*'` in all APIs (`products-api`, `fulfillment-api`, `mcp-order-server`), which is highly insecure for production environments but acceptable for local development/demonstration. There are no obvious hardcoded secrets in the provided snippets, 'eval' usage, or malicious patterns. For production deployment, CORS policies must be restricted, and all inter-service communication should use HTTPS.
Updated: 2025-11-30GitHub→
0
0
Low Cost
stevenwall icon

gfrestaurants-sse

by stevenwall

Sec1

Provides real-time updates and data streaming capabilities for a restaurant multi-channel platform.

Review RequiredView Analysis
Insufficient source code provided (only README.md) to perform a meaningful security audit. Cannot verify the presence of 'eval', hardcoded secrets, network risks, or malicious patterns.
Updated: 2025-12-14GitHub→
0
0
Medium Cost
fab-codes icon

trakt-mcp-server

by fab-codes

Sec9

Provides AI assistants with access to the Trakt.tv API for TV show tracking, watchlist management, and personalized viewing recommendations.

Setup Requirements

  • ⚠️Requires a Trakt.tv account and API credentials (Client ID and OAuth Access Token).
  • ⚠️The OAuth Access Token must have `public`, `read`, and `write` permissions for full functionality.
  • ⚠️Python 3.11+ is required for optimal performance as per `pyproject.toml`.
Verified SafeView Analysis
The server loads sensitive API credentials (Trakt Client ID, Access Token) from environment variables, which is a good security practice. It uses `httpx` with configured timeouts and connection pooling for network requests. Comprehensive error handling is implemented for various API and network issues, including specific handling for 401 (AuthenticationError) and 429 (Rate Limit). There are no 'eval' statements, code obfuscation, or other immediately apparent malicious patterns. The `User-Agent` is hardcoded, which is standard for API clients and not a security risk.
Updated: 2025-12-30GitHub→
0
0
Low Cost
elvetah-cmd icon

mcp-server

by elvetah-cmd

Sec8

A comprehensive Model Context Protocol (MCP) server designed for business affairs professionals in media, entertainment, and production industries, offering data integration, workflow support, task automation, and project context management.

Setup Requirements

  • ⚠️Integrations for Google (Gmail, Drive) and Microsoft (Outlook) are currently placeholders and require manual installation of `googleapis` or `@microsoft/microsoft-graph-client`, along with a complete OAuth 2.0 flow to obtain client IDs, secrets, and refresh tokens. The provided code does not implement the full OAuth flow, only consumes the tokens.
  • ⚠️Specific optional dependencies (`googleapis`, `@microsoft/microsoft-graph-client`, `csv-parser`, `xlsx`) must be manually installed if the corresponding integration tools (e.g., email fetching, budget file import) are to be implemented and used.
  • ⚠️Node.js version 18.0.0 or higher is a prerequisite.
Verified SafeView Analysis
The server correctly uses environment variables for sensitive API keys (e.g., GMAIL_CLIENT_ID, GDRIVE_CLIENT_SECRET), preventing hardcoded secrets. No direct use of `eval` or `child_process` with unsanitized user input was found, reducing command injection risks. The HTTP routes (via Express) are optional and not enabled by default via `npm start`; if enabled, proper authentication and authorization would be critical. Google Drive webhook integration is mentioned as a placeholder, which would require careful security implementation (e.g., signature verification) when fully realized. Input validation in `lib/validators.js` helps prevent malformed data, but robust input sanitation is key for all text processing functions. Overall, the foundational codebase is relatively secure for its stdio-based operation.
Updated: 2025-11-19GitHub→
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