Hue MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap. For example, hue_check_directory_exists verifies existence, hue_list_directory browses contents, hue_download_file handles single files, hue_download_directory handles directories, hue_upload_file uploads, hue_execute_query runs queries, hue_export_and_download handles INSERT queries with downloads, and hue_run_query_to_csv exports directly to CSV. The descriptions clearly differentiate their specific use cases.
Naming Consistency5/5
All tools follow a consistent 'hue_verb_noun' pattern with snake_case throughout. The verbs are descriptive and appropriate for each action (e.g., check, download, execute, export, list, run, upload). There are no deviations in naming conventions across the toolset.
Tool Count5/5
With 8 tools, this server is well-scoped for its purpose of interacting with HDFS and executing queries via Hue. The count covers essential operations like file management (upload, download, list, check) and query execution (execute, export, run to CSV) without being excessive. Each tool serves a clear, necessary function in the workflow.
Completeness4/5
The toolset provides strong coverage for core HDFS file operations and SQL query execution, including CRUD-like actions for files and data retrieval. Minor gaps exist, such as no direct tool for deleting files/directories in HDFS or updating queries, but agents can work around these using existing tools (e.g., overwriting with upload or using INSERT queries). The surface supports common workflows effectively.
Average 4.1/5 across 8 of 8 tools scored. Lowest: 3.5/5.
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
This repository is licensed under MIT License.
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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 provided, the description carries the full burden of behavioral disclosure. It mentions the return type ('OperationResult indicating success') but fails to detail critical aspects like permissions needed, file size limits, overwrite behavior, or error handling, leaving significant gaps 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence earns its place without redundancy, making it efficient and easy to parse.
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 complexity as a file upload operation with no annotations and an output schema, the description is minimally adequate. It covers basic purpose and parameters but lacks behavioral details like side effects or error cases, which are crucial for safe usage in this context.
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?
The description adds meaningful context beyond the input schema, which has 0% coverage. It explains that 'local_file_path' is the source and 'hdfs_destination' is the target directory, clarifying their roles. However, it doesn't specify format details like path syntax or HDFS conventions, slightly limiting completeness.
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 specific action ('Upload a local file to HDFS') with the resource ('local file'), distinguishing it from siblings like download or list operations. It explicitly names the tool's function without being vague or tautological.
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, such as hue_upload_directory (if it existed) or how it relates to siblings like hue_download_file. The description lacks context about prerequisites or exclusions, offering only basic usage without comparative advice.
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 provided, so the description carries the full burden of behavioral disclosure. While it mentions the return type ('OperationResult with the local filename'), it does not cover critical aspects like authentication requirements, error handling, file size limits, network timeouts, or whether the operation is idempotent. For a file download tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 well-structured and front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence adds value without redundancy, making it efficient and easy to parse.
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 has an output schema (which covers return values), the description does not need to explain return details. However, with no annotations and a file operation that could involve permissions, errors, or performance considerations, the description is minimally adequate but lacks depth for safe and effective use in complex scenarios.
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?
The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'remote_path' is 'the full path to the file in HDFS' and 'local_filename' is 'Local filename to save as (optional, defaults to original name)', clarifying usage and default behavior. However, it does not detail path format requirements or validation rules.
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 specific action ('Download a single file') and resource ('from HDFS'), distinguishing it from sibling tools like hue_download_directory (for directories) and hue_upload_file (reverse operation). It precisely defines the tool's scope without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the parameter descriptions (e.g., 'full path to the file in HDFS'), but does not explicitly state when to use this tool versus alternatives like hue_download_directory or hue_export_and_download. It provides clear operational guidance but lacks explicit sibling differentiation.
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?
With no annotations provided, the description carries the full burden. It discloses the boolean return behavior ('True if exists, False otherwise'), which is helpful, but lacks details on error handling, permissions needed, or performance characteristics. It adds some value but misses key behavioral traits for a file system operation.
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 perfectly front-loaded with the core purpose in the first sentence, followed by structured Args and Returns sections. Every sentence earns its place with no wasted words, making it highly efficient and easy to parse.
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?
Given the tool's low complexity (1 parameter, boolean output), the description is largely complete: it states the purpose, parameter meaning, and return value. The output schema exists, so return values needn't be explained. However, it could benefit from more behavioral context (e.g., error cases) to be fully comprehensive.
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?
The schema description coverage is 0%, so the description must compensate. It provides a clear explanation of the single parameter ('directory_path: The HDFS directory path to check'), adding essential meaning beyond the bare schema. This adequately covers the parameter semantics for this simple 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 specific verb ('check if exists') and resource ('directory in HDFS'), distinguishing it from siblings like hue_list_directory (which lists contents) or hue_download_directory (which downloads). It precisely communicates the tool's function without ambiguity.
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 verifying directory existence in HDFS, but lacks explicit guidance on when to use this versus alternatives (e.g., hue_list_directory for more detailed info) or any prerequisites. It provides basic context but no exclusions or comparative advice.
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 carries full burden for behavioral disclosure. It mentions the operation returns an 'OperationResult with list of downloaded files', which adds some context about output format. However, it doesn't address critical behavioral aspects like permissions needed, whether it overwrites existing local files, error handling, or performance implications for large directories.
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 efficiently structured with a clear purpose statement followed by well-organized Args and Returns sections. Every sentence earns its place by providing essential information without redundancy. The formatting enhances readability while maintaining brevity.
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?
Given the tool has an output schema (which handles return values), 3 parameters with no schema descriptions, and no annotations, the description does well by fully documenting parameters and stating the return type. However, as a file transfer operation with potential side effects, it could benefit from more behavioral context about safety and constraints.
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?
With 0% schema description coverage, the description fully compensates by providing clear semantic explanations for all 3 parameters: directory_path specifies the source, local_directory specifies the destination with default, and file_pattern explains filtering with a concrete example. This adds significant value 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 the specific action ('Download all files') and resource ('from an HDFS directory'), distinguishing it from sibling tools like hue_download_file (single file) and hue_list_directory (listing only). The verb+resource combination is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the parameter explanations (e.g., filtering with file_pattern), but doesn't explicitly state when to use this tool versus alternatives like hue_download_file or hue_export_and_download. It provides clear functional context but lacks explicit comparative guidance.
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?
With no annotations provided, the description carries full burden. It discloses key behavioral traits: executes a specific type of SQL query (INSERT OVERWRITE DIRECTORY), writes to HDFS, downloads to local filesystem, and has a timeout default. However, it doesn't mention important aspects like whether the operation is destructive (OVERWRITE implies it might be), authentication requirements, error handling, or rate limits. The description adds value but leaves significant gaps.
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 perfectly structured: a clear purpose statement upfront, followed by context, then a well-organized parameter list with explanations and defaults, and finally the return value. Every sentence earns its place with no redundancy. The information is front-loaded and efficiently presented.
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?
Given 6 parameters with 0% schema coverage and no annotations, the description does an excellent job explaining parameters and stating the return type. However, for a tool that executes queries and downloads files, it lacks information about error conditions, file formats, what happens if the directory already exists, or security implications. The presence of an output schema helps, but behavioral context could be more complete.
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 must compensate. It provides meaningful explanations for all 6 parameters beyond their titles: statement is 'SQL statement with INSERT OVERWRITE DIRECTORY', hdfs_directory is 'The HDFS directory where results are written', local_directory has default '.', dialect options are listed, file_pattern is 'Optional regex pattern to filter files', and timeout is 'Maximum wait time in seconds'. This adds substantial semantic value over 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 the specific action: 'Execute an INSERT OVERWRITE DIRECTORY query and download the results.' It distinguishes from siblings like hue_execute_query (general query execution) and hue_download_directory (download without query execution) by combining both operations. The verb+resource combination is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: 'This tool is for queries that write output to HDFS (like INSERT OVERWRITE DIRECTORY), then downloads the resulting files.' This implicitly distinguishes it from siblings that don't execute queries or don't download. However, it doesn't explicitly state when NOT to use it or name specific alternatives like hue_run_query_to_csv for different output formats.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's core behavior (executing SQL and saving to CSV) and mentions it's for 'large result sets' with batching, but lacks details on permissions, error handling, rate limits, or file system implications. It adds some context but doesn't fully compensate for the absence of annotations.
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 well-structured and appropriately sized. It starts with a clear purpose statement, adds context in the second sentence, and efficiently documents parameters and returns in labeled sections. Every sentence adds value without redundancy, making it easy to parse.
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?
Given the tool's complexity (4 parameters, no annotations, but with an output schema), the description is mostly complete. It explains parameters thoroughly and mentions the return type ('OperationResult'), but since there's an output schema, it doesn't need to detail return values. However, it could better address behavioral aspects like error cases or performance implications.
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 adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'statement' as the SQL to execute, 'filename' as the output CSV file, 'dialect' with allowed values ('hive', 'sparksql', or 'impala'), and 'batch_size' as rows per batch. This fully compensates for the schema's lack of 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 states the tool's purpose with specific verbs ('execute a SQL query and save results directly to a CSV file') and distinguishes it from siblings like 'hue_execute_query' (which doesn't export) and 'hue_export_and_download' (which may have different functionality). The phrase 'convenience method that combines query execution with CSV export' further clarifies its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('ideal for exporting large result sets to files'), but it doesn't explicitly state when not to use it or name specific alternatives among the sibling tools. It implies usage for CSV export scenarios without detailed exclusions or comparisons.
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?
No annotations are provided, so the description carries the full burden. It describes a read-only listing operation, which is clear, but lacks details on permissions, error handling, or rate limits. The mention of pagination (page_size) and return structure adds some behavioral context, but more could be included for a mutation-free tool.
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 well-structured and front-loaded with the core purpose, followed by usage guidance and parameter details. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.
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?
Given the tool's low complexity (2 parameters, no nested objects) and the presence of an output schema (implied by 'Returns' statement), the description is mostly complete. It covers purpose, usage, parameters, and return structure, but could benefit from more behavioral details like error cases or performance considerations to be fully comprehensive.
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 must compensate. It explains both parameters: directory_path as 'The HDFS directory path' with examples, and page_size as 'Maximum number of items to return' with a default. This adds meaningful semantics beyond the bare schema, though it doesn't cover all possible nuances like path validation.
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 'list' and resource 'files and directories in an HDFS path', making the purpose specific and actionable. It distinguishes from siblings like hue_check_directory_exists (checking existence) and hue_download_directory (downloading content), establishing a unique read-only browsing function.
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?
The description explicitly states 'Use this to browse the contents of HDFS directories', providing clear context for when to use this tool. It implies alternatives like hue_check_directory_exists for existence checks or hue_download_directory for downloading, though it doesn't name them directly, but the guidance is sufficient for effective tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: executing a SQL statement, waiting for completion, fetching all results, and handling pagination via batch_size. It also implies potential timeouts and resource usage, though it could add more on error handling or permissions.
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 well-structured and front-loaded, starting with the core purpose, followed by usage guidance, and then detailed parameter explanations. Every sentence adds value without redundancy, making it efficient and easy to scan for an AI agent.
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's complexity (4 parameters, no annotations, but with an output schema), the description is complete enough. It covers purpose, usage, parameters, and return values ('QueryResult with headers, rows, and row_count'), and the output schema eliminates the need to detail return formats further, ensuring the agent has all necessary context.
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 adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose, provides examples (e.g., SQL statement format), lists dialect options, and clarifies defaults and units (seconds for timeout, rows for batch_size). This fully compensates for the schema's lack of 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 states the tool's purpose with a specific verb ('execute a SQL query'), resource ('on Hue'), and outcome ('return the results'). It distinguishes from siblings by focusing on direct SQL execution rather than file operations or directory checks, making it immediately identifiable for its intended use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by specifying 'Use this for SELECT queries where you want to retrieve data,' which helps differentiate it from potential write operations. However, it does not explicitly mention when not to use it or name alternatives among siblings, such as 'hue_run_query_to_csv' for CSV output, leaving some ambiguity.
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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