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Vetted Servers(9120)

0
0
Low Cost
annmalavet icon

MCP-SERVER-DB

by annmalavet

Sec8

This server provides a Model Context Protocol (MCP) endpoint that exposes a 'search_database' tool for querying a PostgreSQL database for people by email or major.

Setup Requirements

  • ⚠️Requires an accessible PostgreSQL database instance.
  • ⚠️Critical environment variables (DB_USER, DB_PASS, DB_NAME, DB_HOST, DB_PORT) for PostgreSQL connection must be configured. Note that the default DB_PORT value (8080) in the code is unlikely to be the correct PostgreSQL port and will conflict with the application's default listening port.
  • ⚠️Node.js runtime version 18 or higher is required.
Verified SafeView Analysis
The server uses parameterized SQL queries to interact with the database, effectively preventing SQL injection vulnerabilities. However, it directly exposes raw database error messages to the client, which can be an information disclosure risk, potentially revealing internal database structure or query failures.
Updated: 2026-01-11GitHub→
0
0
Low Cost
zuologio icon

McpWeatherServer

by zuologio

Sec6

A server application designed to provide weather information to connected clients, likely within a Minecraft Coder Pack (MCP) environment.

Setup Requirements

  • ⚠️Requires Java Development Kit (JDK) 8+ to compile and run.
  • ⚠️Requires an available network port for the server to listen on.
Verified SafeView Analysis
The server appears to lack explicit authentication, authorization, or encryption for network communication, which are common risks for networked services. Input validation in ServerHandler.java is assumed but not confirmed, potentially leading to malformed request vulnerabilities. No 'eval' or obvious malicious patterns are evident from the provided summary. It is likely intended for controlled or local environments, which mitigates some public exposure risks.
Updated: 2025-12-01GitHub→
0
0
High Cost
madking2099 icon

grok_mcp_setup

by madking2099

Sec8

Integrate Grok (via CodeGPT) with local Git repositories, self-hosted web search, and a local document library through Dockerized Model Context Protocol (MCP) servers.

Setup Requirements

  • ⚠️Requires Docker and Docker Compose (v2+) installed.
  • ⚠️Requires CodeGPT plugin in PyCharm with an xAI API key for Grok integration.
  • ⚠️Requires manual creation and provisioning of `pdf_server.py` for full PDF extraction functionality within the library service. The provided setup only includes a stub.
  • ⚠️Local directories (`PROJECTS_PATH`, `LIBRARY_PATH`) must be mounted to containers for data access.
Verified SafeView Analysis
The setup employs good security practices like read-only volumes (`:ro`) for mounted directories (`/projects`, `/ebooks`) and whitelisting of allowed paths (`--allowed-paths`). It avoids direct `eval` or `os.system` with shell=True in the provided scripts. However, the `mcp-lib` service's PDF extraction relies on a user-provided `pdf_server.py` script; its security is dependent on the user's implementation, which could introduce vulnerabilities if not carefully written. The `BRAVE_API_KEY` is a placeholder, indicating a sensitive variable that needs secure management if enabled for the bundled version.
Updated: 2025-11-30GitHub→
0
0
Low Cost
skylukas1 icon

claude.mcp.test

by skylukas1

Sec1

Acts as a Master Control Program (MCP) server designed to execute custom commands, typically exposed via a network tunnel.

Setup Requirements

  • ⚠️Requires ngrok for public exposure and tunneling.
  • ⚠️The actual server implementation code is not provided, meaning the core server logic needs to be obtained or written before it can be run.
Review RequiredView Analysis
Critical: No server source code was provided for analysis beyond the README. Therefore, a security audit cannot be performed to check for vulnerabilities such as 'eval' usage, obfuscation, network risks, hardcoded secrets, or malicious patterns. Running this server without access to and an audit of its implementation code is highly insecure as its behavior and security posture are unknown.
Updated: 2025-12-12GitHub→
0
0
Medium Cost
scanady icon
Sec8

Manages engineering standards, practices, and processes, providing AI assistants with structured access to an organization's knowledge base.

Setup Requirements

  • ⚠️Requires Node.js >= 18.0.0
Verified SafeView Analysis
The server uses `fs.promises` for file system operations (read, write, delete, rename) within a configurable `STANDARDS_DIR`. Input validation is performed using Zod schemas, and path/filename sanitization (`normalizeTargetPath`, `sanitizeFilename`) is implemented to mitigate path traversal risks. The `create_standard` and `update_standard` tools are explicitly marked as 'destructive'. No direct use of `eval` or similar dangerous functions, nor any obvious hardcoded secrets, was found. The Docker configuration enforces running as a non-root user (UID 1001).
Updated: 2025-12-11GitHub→
0
0
High Cost
agileguy icon
Sec9

A Model Context Protocol (MCP) server that enables AI assistants to query and retrieve Google Kubernetes Engine logs from Cloud Logging.

Setup Requirements

  • ⚠️Requires Python 3.11+.
  • ⚠️Requires a Google Cloud Project with GKE clusters and appropriate IAM roles (logging.viewer, container.clusterViewer).
  • ⚠️Requires authentication to GCP (e.g., via 'gcloud auth application-default login' for local development or Workload Identity for Kubernetes deployment).
Verified SafeView Analysis
The server implements robust input validation for resource names and filter strings to prevent injection attacks. It uses minimal IAM permissions ('roles/logging.viewer', 'roles/container.clusterViewer'). Production deployments leverage Kubernetes Workload Identity, run as a non-root user with a read-only root filesystem, drop all capabilities, and include Network Policies to restrict traffic. No direct 'eval' or 'exec' with user-controlled input is present. The regex used for pod names and search text is passed to the Cloud Logging API, relying on GCP's security for filter evaluation.
Updated: 2025-11-30GitHub→
0
0
High Cost
Bandwidth icon

mcp-server

by Bandwidth

Sec9

The Bandwidth Official MCP Server enables AI agents to interact with various Bandwidth APIs for communication services, allowing programmatic control over messaging, voice, MFA, and compliance operations.

Setup Requirements

  • ⚠️Requires valid Bandwidth API Credentials (BW_USERNAME, BW_PASSWORD, BW_ACCOUNT_ID). These typically imply a paid Bandwidth account.
  • ⚠️Specific functionalities require additional Bandwidth IDs (e.g., BW_MESSAGING_APPLICATION_ID, BW_VOICE_APPLICATION_ID) and a valid phone number (BW_NUMBER), which are conditionally required environment variables.
  • ⚠️Requires Python 3.10+.
  • ⚠️Requires 'uv' (a Python package installer and runner) to be installed, or manual virtual environment setup with pip.
Verified SafeView Analysis
The server follows good security practices by loading sensitive API credentials from environment variables. It fetches OpenAPI specifications from hardcoded, trusted Bandwidth URLs and includes a cleaning step to remove potentially dangerous 'callbacks' and 'x-' fields from the spec, reducing the risk of malicious spec injection. Authentication uses standard Basic HTTP authentication over HTTPS. No obvious 'eval' or malicious patterns were found in the provided source code.
Updated: 2025-12-05GitHub→
0
0
Low Cost
Sec5

A Python-based application server, likely designed to serve or manage categorized data, or function as a proxy.

Setup Requirements

  • ⚠️Requires `uv` to be installed for dependency management and execution.
  • ⚠️Specific Python version required, as defined in the `.python-version` file.
Review RequiredView Analysis
Code not provided for analysis; therefore, specific vulnerabilities like 'eval' or obfuscation cannot be confirmed. As a server application, it inherently exposes network services, which always carries a general level of risk.
Updated: 2025-11-18GitHub→
0
0
Medium Cost
Vinni-Anddrade icon

mcp-server-and-ai

by Vinni-Anddrade

Sec1

A server implementation with integrated AI capabilities, likely for a game or simulation environment.

Review RequiredView Analysis
A comprehensive security audit is impossible due to the complete lack of provided source code for analysis. Without code, no assessment of 'eval', obfuscation, network risks, hardcoded secrets, or malicious patterns can be made.
Updated: 2025-11-25GitHub→
0
0
Medium Cost
drkhannah icon
Sec8

This server provides an agent-enabled memory system, allowing an MCP agent to save and retrieve information using OpenAI's vector store capabilities.

Setup Requirements

  • ⚠️Requires OpenAI API Key (Paid Service)
  • ⚠️Python 3.12+ required
Verified SafeView Analysis
The server writes user-provided 'memory' directly to a temporary file and uploads it, and passes 'query' directly to OpenAI's search API. While there's no direct local code execution vulnerability, an attacker could potentially craft malicious inputs to exploit unforeseen vulnerabilities in OpenAI's file processing or search functionality.
Updated: 2025-11-28GitHub→
0
0
Medium Cost
46ki75 icon

mcp-rust-docs

by 46ki75

Sec9

This server provides AI agents with tools to search for Rust crates on crates.io and retrieve detailed documentation from docs.rs.

Verified SafeView Analysis
The server primarily performs HTTP GET requests to public APIs (crates.io, docs.rs) and parses the HTML/JSON responses. It uses standard Rust libraries (`reqwest`, `crates_io_api`, `scraper`, `html2md`, `tantivy`). There are no signs of direct command execution, `eval` usage, hardcoded secrets, or obfuscation. User inputs for crate names, versions, and paths are used to construct URLs for docs.rs; while direct injection is mitigated by the nature of HTTP GET and docs.rs's expected handling of invalid paths, it's good practice to ensure inputs are well-formed. The fuzzy search uses a temporary directory for its index, which is a secure practice.
Updated: 2026-01-16GitHub→
0
0
Low Cost
dmmulroy icon

opensrc-mcp

by dmmulroy

Sec9

A codemode MCP server for fetching and querying dependency source code, optimized for AI agents.

Setup Requirements

  • ⚠️Requires Node.js and npm/npx installed on the system.
  • ⚠️Requires an OpenCode client (or similar agent framework) configured to use this MCP server locally.
  • ⚠️Fetched source code and metadata are stored in an `opensrc/` directory within your project, consuming local disk space.
Verified SafeView Analysis
The server employs robust sandboxing using Node.js's `vm.createContext` to execute agent-provided JavaScript. Key security measures include: `deepFreeze` of injected API objects to prevent modification, explicit disabling/undefined of dangerous global functions (`setTimeout`, `require`, `process`, `fetch`, etc.) to prevent arbitrary system access or network calls, a 30-second execution timeout to prevent infinite loops, and explicit path traversal prevention in file reading functions. External network operations (fetching packages/repos) are handled by the server's controlled `opensrc` dependency. While `vm` sandboxes are not entirely infallible against sophisticated attacks, this implementation is highly secure for its intended purpose of executing untrusted JavaScript code.
Updated: 2026-01-19GitHub→
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