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Nuvepro-Technologies-Pvt-Ltd

Lab Virtual MCP Server

by Nuvepro-Technologies-Pvt-Ltd
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

execution in a secure and scalable lab setup.

⚙️ Lab Virtual MCP Server (Execute Code Remotely via Claude AI) Create a virtual lab for users to run custom code remotely using the Model Context Protocol (MCP) and integrate with Claude AI or other clients.

🔗 GitHub Repo

📂 This repo has moved to base/base-mcp

🚀 What This Lab Server Does 🧠 Enables remote Python code execution through cline AI

🧪 Supports real-time lab scenarios (code evaluation, sandbox testing, etc.)

📋 Prerequisites Ensure you have the following on your system:

✅ Python 3.10.11

✅ pip (Python package manager)

✅ fastmcp (to serve the MCP endpoint)

✅ uv (virtual environment manager, via scoop or curl)

✅ Access to Claude Desktop or Cursor or cline (for testing)

🧱 Installation Steps

  1. Clone the MCP Server Repo

  1. Set up Python Environment

cd McpSever_Remote_code_execution

  1. Set Up Virtual Environment

  1. Install Dependencies

  1. Run the Server

You now have a remote code execution server listening for requests via MCP.

🧪 MCP Client Configuration For Claude Desktop / Cursor, update your mcp_config.json:

Beofre start Mcp set path

✅ Available Tools (Prebuilt in MCP)

Tool Description execute_code Executes user-provided Python code

💡 Recommendations for Lab Admins ✅ Add sandboxing logic to app.py if users can run arbitrary code.

✅ Use Docker or subprocess isolation for safer execution (optional).

✅ Monitor logs and set execution timeouts.

Available Tools

1 tool
execute_codeC

Execute code in a secure sandbox environment.

ParametersJSON Schema
NameRequiredDescriptionDefault
payloadNo
filepathNo
latest_generatedNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions a 'secure sandbox environment', which hints at isolation and safety, but lacks details on permissions, rate limits, output handling, or error behavior. This is a significant gap for a code execution tool with no structured safety hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste, clearly stating the core function. It is appropriately sized and front-loaded, making it easy to parse without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of code execution, no annotations, 0% schema coverage, but an output schema exists, the description is incomplete. It covers the basic purpose but misses critical details like behavioral traits, parameter meanings, and execution constraints. The output schema may help with return values, but overall, it's minimally adequate with clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate for three undocumented parameters. It adds no meaning beyond the tool name, failing to explain parameters like 'payload', 'filepath', or 'latest_generated'. This leaves the agent guessing about input semantics, resulting in poor parameter guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose as executing code in a secure sandbox environment, which is clear but vague. It specifies the action (execute code) and context (secure sandbox), but lacks details on what type of code, languages supported, or execution scope, making it moderately informative but not specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool, such as scenarios for execution, prerequisites, or alternatives. With no sibling tools, it doesn't need to differentiate, but it fails to offer any usage context, leaving the agent without direction on appropriate application.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev0.1.0
    • First observedexecute_code
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TDQS

C2.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'execute_code' has a clear, distinct purpose that cannot be confused with any other tool in the set.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'execute_code' follows a clear verb_noun pattern, which would be consistent if more tools were added.

Tool Count2/5

One tool is generally too few for a server's purpose, as it limits functionality and may not cover the domain adequately. For a 'Lab Virtual MCP Server' that likely involves code execution, additional tools for managing environments, listing sessions, or handling inputs/outputs would be expected.

Completeness1/5

The tool set is severely incomplete for the inferred domain of a lab or virtual environment. With only an 'execute_code' tool, there are obvious gaps such as creating or deleting environments, listing available sessions, handling file uploads/downloads, or monitoring execution status, which are essential for a coherent workflow.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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