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iota-uz

repl-mcp

by iota-uz
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v2.1.1

  • 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.

  • Average 5/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • 0 of 8 community issues answered or closed in the last 6 months
    • 17 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

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  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior5/5

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

    With no annotations provided, the description carries the full burden. It discloses state persistence across calls, filesystem access, top-level await support, timeout enforcement with KeyboardInterrupt and namespace preservation, and the behavior of the reset parameter. These go well beyond what the schema offers and provide critical safety/behavioral context.

    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 front-loaded with the core purpose ('Persistent Python REPL') and then expands with necessary details. Every sentence earns its place: performance comparison, state persistence, filesystem access, await support, and timeout behavior. It is dense yet well-structured, with no fluff.

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

    Completeness5/5

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

    Given the tool complexity (persistent REPL, filesystem access, MCP bridge) and lack of output schema, the description covers all essential invocation details: what it does, when to use it, persistent state, async support, timeout behavior, and reset semantics. It is sufficiently complete for an agent to invoke the tool correctly.

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

    Parameters5/5

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

    Although schema coverage is 100%, the description adds substantial meaning to the `code` parameter by explaining persistent state, await support, and the injected `mcp` bridge, which are not conveyed by the schema's generic 'Python code to execute'. This enriches the agent's understanding of how to write effective code for this tool.

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

    Purpose5/5

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

    The description clearly states the tool is a persistent Python REPL, distinguishing it from one-off bash execution via `python3 -c`. It uses a specific verb ('execute') and resource ('Python code') while also noting the persistent state and MCP bridge capabilities, which clearly differentiates it from sibling tools even though none are listed.

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

    Usage Guidelines5/5

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

    It explicitly says to use this tool instead of `python3 -c`, heredocs, or `cmd | python3` via Bash, with a concrete performance justification (warm call ~0.1s vs ~3s). It also explains when it's beneficial for batch MCP work, providing clear usage context and alternatives.

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

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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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