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Glama
iota-uz

repl-mcp

by iota-uz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
execute_pythonA

Persistent Python REPL — use instead of python3 -c, heredocs or cmd | python3 via Bash. Also the way to BATCH MCP WORK: the injected mcp bridge reaches your project, global (user-scope) and plugin MCP servers, so one loop replaces N separate tool calls — for f in files: mcp.call('telegram-mcp', 'download_media', **f).

State (variables, imports, functions) survives across calls: a warm call takes ~0.1s vs ~3s for each fresh python3 Bash spawn. Full filesystem access — open(), absolute paths, and ~ all work. Top-level await is supported (e.g. await client.get(url) with httpx).

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.9/5.0

Scored across 1 tool

Disambiguation5/5

Only one tool exists, so there is zero ambiguity. The tool's purpose as a persistent Python REPL is clearly defined and distinct from any other tool.

Naming Consistency5/5

The single tool name 'execute_python' follows a clear verb_noun pattern in snake_case. With only one tool, consistency is inherently maintained.

Tool Count4/5

One tool is slightly below the typical 3-15 range, but for a REPL server it is appropriate. The tool consolidates execution, state persistence, filesystem access, and MCP calls into a single well-designed interface.

Completeness5/5

The tool covers the entire REPL domain: arbitrary Python execution, persistent state, top-level await, full filesystem access, and MCP integration. There are no apparent dead ends or missing operations.

Maintenance

ActivitySlowing
ResponsivenessUnresponsive

Resources