Search Results for "linux secure"
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Showing 7 open source projects for "linux secure"
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MCP Shell Server
Shell command execution server implementing the Model Context Protocol
A secure shell command execution server implementing the Model Context Protocol (MCP), allowing remote execution of whitelisted shell commands with support for standard input. -
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MCP Atlassian
MCP server that integrates Confluence and Jira
The MCP Atlassian server integrates Atlassian products like Confluence and Jira with the Model Context Protocol. It supports both Cloud and Server/Data Center deployments, enabling AI models to interact with these platforms securely. -
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Upsonic
The most reliable AI agent framework that supports MCP
Upsonic is a reliability-focused AI agent framework designed for real-world applications. It enables the development of trusted agent workflows within organizations by incorporating advanced reliability features, such as verification layers and output evaluation systems. The framework supports the Model Context Protocol (MCP), facilitating integration with various tools and enhancing agent capabilities. -
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mcpo
A simple, secure MCP-to-OpenAPI proxy server
mcpo is a minimal bridge that exposes any MCP tool as an OpenAPI-compatible HTTP server. Instead of writing glue code, you point mcpo at an MCP server command and it generates REST endpoints and an OpenAPI spec that other systems (or LLM agent frameworks) can call immediately. This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI... -
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MCP Snowflake Server
A Model Context Protocol (MCP) server implementation
An MCP server implementation that facilitates database interactions with Snowflake, allowing execution of SQL queries and presentation of data insights as resources. -
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Colab-MCP
An MCP server for interacting with Google Colab
Colab-MCP is an open-source Model Context Protocol server developed by Google that enables AI agents to directly interact with and control Google Colab environments programmatically, transforming Colab into a fully automated, agent-accessible workspace. Instead of relying on manual notebook usage, the system allows MCP-compatible agents to execute code, manage files, install dependencies, and orchestrate entire development workflows within Colab’s cloud infrastructure. This approach bridges... -
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LitterBox
A secure sandbox environment for malware developers and red teamers
LitterBox is a controlled malware-analysis and payload-testing sandbox aimed at red teams who need to validate evasions and behaviors before deployment. It provides an isolated environment to exercise payloads against modern detection stacks, verify signatures and heuristics, and observe runtime characteristics without leaking binaries to third-party vendors. The README frames typical use cases: testing evasion, validating detections, analyzing behavior, and keeping sensitive tooling...
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