STUzhy-py_execute_mcp
Server Details
Run Python code in a secure sandbox without local setup. Declare inline dependencies and execute s…
- Status
- Unhealthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
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Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 2.9/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of ambiguity or confusion between tools. The single tool has a clearly defined purpose: executing Python code in a sandbox with optional requirements.
There is only one tool, so naming consistency is inherently perfect. The tool name 'python_execute' follows a clear verb_noun pattern, though no comparison with other tools is possible.
A single tool is too few for most practical server purposes, as it severely limits functionality and flexibility. While the tool is well-defined, the server's scope feels thin and incomplete with only one operation available.
For a Python execution server, there are obvious gaps: no tools for managing code files, inspecting results, handling errors, or providing additional sandbox controls. The single tool covers only basic execution, leaving significant functionality missing for a robust Python environment.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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