MCP Python Interpreter

by luutuankiet

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct operation: package installation, listing, environments, code execution (inline/file), file read/write, and listing Python files. There is no overlap, and descriptions clearly differentiate similar tools like run_python_code and run_python_file.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., install_package, list_directory, run_python_code). No deviations or mixed conventions.
Tool Count5/5
With 9 tools, the set is well-scoped for a Python interpreter server. It covers essential operations without being overwhelming or too sparse.
Completeness4/5
Core workflows (install, run, read/write files, list environments) are covered. Minor gaps include missing uninstall_package and more detailed environment management, but the set is sufficient for common tasks.
Average 3.4/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions 'Code runs in the working directory' but does not disclose potential side effects (e.g., file modification), security implications, or what 'return the result' means (stdout/stderr/return value). Minimal behavioral disclosure for an execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the main action. Parameter descriptions are in a clear list. No unnecessary words. However, a slightly longer description with behavioral details would not harm conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and moderate complexity, the description lacks details on return values, error handling, security, and alternatives (vs run_python_file). Not complete for an execution tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It adds context for each parameter: code (the code to execute), environment ('Name of the Python environment...'), and save_as (optional filename). This adds value beyond the schema, but details are vague (e.g., 'custom path provided' unspecified, 'system' environment unclear).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Execute Python code and return the result' with a specific verb+resource. It also mentions execution context ('working directory'). However, it does not explicitly differentiate from sibling tools like run_python_file, so it's not a perfect 5.
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?
No guidance on when to use this tool versus alternatives. No context about prerequisites, typical use cases, or exclusions. The description only explains the parameters, not usage strategy.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes mutation ('write') but fails to disclose error handling (e.g., behavior when file exists and overwrite=False), permission requirements for 'system-wide', or side effects. The return value is not described.
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?
Extremely concise: one-sentence purpose followed by a clearly formatted parameter list. No extraneous information, and the key action is front-loaded.
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?
Covers basic purpose and parameters but lacks error handling info, sibling differentiation, and behavioral details. Given no output schema or annotations, completeness is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description partially compensates with 'Args:' section offering basic parameter descriptions (path, content, overwrite). These add minimal meaning beyond schema names but lack depth, such as format constraints or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'write' and resource 'Python file', and mentions scope (working directory or system-wide). It distinguishes from sibling 'write_file' by specifying 'Python', but doesn't explicitly contrast with other siblings like 'run_python_file'.
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?
No guidance on when to use this tool versus alternatives (e.g., 'write_file' for non-Python files, 'run_python_file' for execution). The description only lists parameters without usage context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It mentions file path resolution and environment defaults, but lacks disclosure of side effects, security implications, error behavior, or whether execution is synchronous. For a tool that runs arbitrary code, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise—one sentence plus a structured Args block. Every part is functional with no fluff. Could be slightly more streamlined but is well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description should cover return format, error handling, and prerequisites (e.g., file existence, Python availability). It does not mention what is returned, side effects, or safety concerns, leaving significant gaps for a file execution tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates well. It explains each parameter's purpose and constraints, such as path relativity and environment resolution. This adds significant meaning beyond the bare schema.
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 'Execute a Python file and return the result', which is a specific verb+resource combination. It distinguishes from sibling 'run_python_code' by focusing on files rather than code strings, and from other siblings like read/write or install tools.
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?
No explicit guidance on when to use this tool versus alternatives like run_python_code or list_directory. The description infers usage for executing a Python file but does not discuss prerequisites, when to avoid, or comparison with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Mentions overwrite and encoding defaults, but omits behaviors like creating directories, appending, or error handling. Insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise description followed by structured Args list. Focused and easy to parse, though the Args section could be integrated into the main description.
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?
Return type mentioned (status message) but no output schema. Lacks details on intermediate directory creation, error cases, or performance implications. For a file write tool, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description adds meaning for all 4 parameters: file_path, content, overwrite (with default false), encoding (with default utf-8). Provides clear context beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it writes content to a file, with context about working directory vs system-wide. Differentiates from read_file and write_python_file, though could be more explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage by mentioning system-wide access, but lacks explicit guidance on when to use this tool versus alternatives like write_python_file. No exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey behavioral traits. It only states that environments are listed, but does not disclose whether the operation is read-only, how the output is structured, or any potential side effects. Minimal value added beyond the basic function.
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, concise sentence that is front-loaded with the key action and resource. Every word is necessary, and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no parameters and no output schema, the description does not elaborate on the return format or any additional context. The agent is left to infer what a list of environments looks like, which is insufficient for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema description coverage is trivially 100%. The description adds no parameter information, but per guidelines, 0 parameters yields a baseline of 4.
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 action ('List') and the resource ('all available Python environments'), with specific mention of 'system Python and conda environments', distinguishing it from sibling tools like list_installed_packages.
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?
No guidance is provided on when to use this tool versus alternatives. The description does not mention any context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description should fully disclose behavior. However, it does not detail what constitutes installed packages, return format, or prerequisites, only a vague default logic for environment parameter.
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?
Extremely concise with one sentence and a parameter description, no unnecessary words.
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 tool's simplicity (one optional param, no output schema, no annotations), the minimal description might suffice but lacks details like listing all packages globally or per environment, version info, and how to specify custom paths.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter, schema description coverage is 0%, but the description adds some meaning by explaining default behavior ('default if custom path provided, otherwise system'). Still lacks full clarity on how environment is resolved.
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?
Description clearly states 'List installed packages for a specific Python environment' with a verb and resource, and distinguishes from siblings like install_package and list_python_environments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for listing packages in a Python environment but provides no explicit when-to-use or when-not-to-use guidance, nor alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry full behavioral disclosure. It only states 'Install a Python package', omitting critical details such as network requirements, system modifications, required permissions, or potential side effects. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a one-line summary followed by parameter details. It is front-loaded and contains no extraneous information, though it could be slightly more compact.
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?
No output schema is provided, so the description should cover return values or status indicators, but it does not. It also lacks mention of dependencies (e.g., pip, internet) or environment restrictions. Overall, it is adequate but leaves gaps for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning parameters have no schema descriptions. The description adds value by explaining each parameter's meaning, including defaults and behavior (e.g., environment fallback, upgrade flag). This adequately compensates for the missing schema descriptions.
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 specifies the verb 'Install' and resource 'Python package', and it distinguishes from sibling tools like list_installed_packages and list_python_environments by focusing on installation rather than inspection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool's function but does not provide guidance on when to use it versus alternatives, nor does it mention prerequisites or when to avoid it. The 'upgrade' parameter hints at conditional usage, but explicit context is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It does not mention recursion depth, performance implications, error handling, or permissions. The phrase 'in a directory or subdirectory' is ambiguous regarding whether it is recursive.
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 extremely concise: one sentence for purpose and one line for the parameter. It is front-loaded with the action, and every part is necessary.
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?
The tool is simple (one param, no output schema), yet the description lacks return format information (e.g., list of paths or names). It also does not specify whether subdirectory traversal is recursive, which is a key behavioral detail.
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?
The description provides full semantic meaning for the only parameter, directory_path: it describes relative/absolute paths and the special empty case for working directory. This adds crucial context beyond the bare schema.
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 uses a specific verb 'List' and resource 'Python files', and clarifies the scope 'in a directory or subdirectory'. This clearly distinguishes it from siblings like read_file or install_package.
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?
No guidance is given on when to use this tool versus alternatives. For example, it does not compare with read_file for reading file contents or list_installed_packages for packages.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses file path handling and size limits but lacks details on error behavior (e.g., file not found, permissions), encoding, or binary file handling.
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 concise, front-loaded with purpose, and structured with Args/Returns. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple file read tool, the description covers essential context. Missing details on what happens when size limit is exceeded or error types, but sibling tools provide differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds significant value by explaining file_path as relative/absolute and max_size_kb with default. Could further clarify supported file types.
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 verb 'Read' and the resource 'file', and the specific functionality of reading with size limits. It distinguishes from sibling tools like write_file and run_python_file.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reading files with size limits but does not explicitly specify when to use this tool over alternatives, nor provides exclusion criteria or prerequisites.
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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