Log MCP Server

by thhart

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no ambiguity: list_log_files identifies available logs, get_log_content retrieves full log content, read_log_paginated handles large files with pagination, and search_log_file performs pattern-based searches. The descriptions explicitly differentiate them, such as warning about using read_log_paginated for large files instead of get_log_content.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (e.g., get_log_content, list_log_files) with clear, descriptive names that use snake_case uniformly. There are no deviations in naming conventions, making the set predictable and easy to understand.
Tool Count5/5
With 4 tools, this server is well-scoped for its log management purpose, covering essential operations like listing, reading, paginating, and searching logs. Each tool earns its place without redundancy, and the count is appropriate for the domain, avoiding both thinness and bloat.
Completeness4/5
The tool surface is nearly complete for log inspection, covering key workflows from discovery to detailed analysis. A minor gap exists in write operations (e.g., creating or clearing logs), but this is reasonable for a read-focused debugging server, and agents can work around it as the core functionality is well-covered.
Average 3.9/5 across 4 of 4 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
- Last stable release on December 8, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states basic behavior (search, return matches with context, pagination). It does not disclose side effects (e.g., file access permissions), performance, or error handling for missing files or invalid patterns.
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?
Two sentences, both front-loaded with core purpose and a key feature. No wasted 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?
Despite 9 parameters and no output schema, the description provides a decent high-level view but omits parameter interdependencies (e.g., max_tokens vs max_matches deprecation). It is adequate but incomplete for a complex 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 100% with detailed parameter descriptions. The description adds minimal extra meaning beyond the schema, just mentioning token-based pagination. Baseline 3 is appropriate.
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 tool searches a log file with regex and returns matching lines with context, which is specific. However, it does not explicitly differentiate from siblings like 'find_errors' or 'read_log_paginated', though regex search is implied as distinct.
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 mentions token-based pagination for AI context limits, giving a usage hint, but lacks explicit when-to-use or when-not-to-use guidance compared to siblings. No alternatives are named.
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 provided, so description carries full burden. It lists error patterns searched but does not disclose return format, performance guarantees, or whether the tool modifies files. Adequate but not detailed.
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?
Two sentences front-load purpose and ideal use. No filler, every word adds value.
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?
Without output schema, description does not explain what the tool returns (e.g., lines with context, format). Among 7 sibling tools, no differentiation guidance beyond the listed patterns. Adequate for simple use but incomplete for an agent needing return structure.
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?
Input schema has 100% coverage with descriptions for all 4 parameters. The tool description does not add extra meaning to parameters; it lists error patterns used internally, which is not about parameter values. Baseline 3 is appropriate.
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 finds error lines in a log file by matching specific patterns (ERROR, Exception, etc.), distinguishing it from sibling tools like search_log_file which may support generic queries.
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 says 'Ideal for quick diagnostics,' implying a use case, but does not specify when to use other tools or exclude scenarios. No guidance on when not to use or alternatives.
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?
Discloses token-based pagination behavioral trait, but without annotations, missing details on destructiveness (assumed read-only), error handling, auth requirements, or output format.
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?
Two concise sentences, front-loaded with essential information, no fluff.
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?
Adequate for a simple read tool but lacks output format description and clear differentiation from read_log_paginated, which also uses pagination.
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 100%; description adds no new meaning beyond the parameter descriptions already in the 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?
Clearly states it reads the beginning of a log file, analogous to Unix 'head'. Differentiates from siblings like tail_log and read_log_paginated by specifying start-of-file orientation.
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 via Unix 'head' analogy and mentions token-based pagination for AI limits, but no explicit guidance on when to use this vs siblings like read_log_paginated or tail_log.
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?
The description discloses token-based pagination to respect AI context limits, which is critical for correct invocation. However, it fails to explain the interaction between the 'lines' and 'max_tokens' parameters, and no annotations are provided to indicate the operation is read-only.
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?
Two concise sentences that front-load the purpose and key behavior. Every sentence carries distinct information with no redundancy.
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 description covers core purpose and an important behavior (token pagination). However, it omits error handling, return format, and the exact interplay between 'lines' and 'max_tokens', leaving some gaps for an agent.
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 provides full coverage for all three parameters. The description adds value by explaining the token-pagination context for max_tokens and likening the tool to the Unix 'tail' command, which aids understanding of the lines parameter.
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 reads the end of a log file using a Unix 'tail' analogy, and distinguishes itself from siblings like head_log and read_log_paginated by explicitly mentioning token-based pagination for AI context limits.
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 phrase 'Ideal for checking recent log entries' implies when to use, but there is no explicit guidance on when not to use or how to choose among siblings like search_log_file or find_errors.
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, and description only mentions returning content. Lacks disclosure of error handling, permissions, or what happens if file is missing. Missing behavioral details expected for a read operation without 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?
Three concise sentences: core function, usage context, alternative. No unnecessary words.
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?
Simple tool with 2 params and no output schema. Description covers directory, purpose, and large file alternative. Lacks error condition details but otherwise complete for its complexity.
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 100%, so baseline is 3. Description adds minor value by clarifying token estimation ('~4 chars per token') and default/max values already in 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?
Description clearly states 'Returns the content of a specific log file from $XDG_RUNTIME_DIR/log' and positions it for debugging. Distinguishes from sibling read_log_paginated.
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?
Explicitly states when to use ('when debugging errors or investigating problems') and provides an alternative for large files with 'use read_log_paginated instead'.
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?
No annotations are provided, so the description carries full burden. It discloses token-based pagination, default and max tokens, character-per-token estimation, and behavior when end_line is unspecified. This adds meaningful context beyond basic read functionality.
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?
Two sentences, each adding essential information. The first sentence states the primary purpose, the second explains key behavioral constraint. No wasted words.
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?
With 4 fully documented parameters and no output schema, the description covers the main behavioral aspects. It lacks error handling details or output format, but for a simple read tool with sibling context, it is reasonably complete.
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 100%, so parameters are already well-documented. The description adds minor value by contextualizing max_tokens and pagination, but does not significantly enhance understanding of individual parameters beyond 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 'Reads a specific range of lines from a log file,' specifying the verb and resource. It differentiates from siblings like head_log or tail_log by focusing on a range, and mentions token-based pagination, which adds context.
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 line ranges with pagination but does not explicitly advise when to use this tool versus alternatives like read_log_paginated or head_log. No exclusions or prerequisites are given.
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 provided, so description carries full burden. It minimally describes behavior (listing files) but doesn't disclose potential performance or side effects. For a zero-parameter read-only tool, this is acceptable but not exemplary.
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?
Two sentences that are clear and front-loaded, but the second sentence partly restates the entry point concept. Minor redundancy but still efficient.
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 zero parameters, no output schema, and a clear purpose, the description fully informs an agent about what the tool does and when to use it.
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?
No parameters exist, and schema coverage is 100%. The description adds no additional semantic information about the output format or contents of the list.
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 'lists', the resource 'log files', and the location. It distinguishes itself from siblings by positioning itself as the entry point for log inspection.
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?
Explicitly specifies when to use this tool first, listing relevant user intents and framing it as the discovery step before other log tools.
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?
Without annotations, the description carries the burden. It discloses key behaviors: token-based pagination, change tracking via expected_size and expected_mtime. This goes beyond simple read into operational details. No contradiction with missing annotations. However, it does not mention error states or side effects, slightly lowering the score.
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?
Three sentences, each dense with information. No fluff. Front-loaded with the primary action. Every sentence earns its place.
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?
With no output schema, the description should explain return values. It implies change tracking results but not explicitly. The parameter richness (6 params) is well-covered by schema, so overall adequate but lacks output format clarity. Still, it's reasonably complete for an agent.
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 100%, so baseline is 3. The description adds no per-parameter semantics beyond what the schema already provides. It mentions overall behaviors (pagination, change tracking) but not parameter-specific meaning.
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 it reads a paginated portion of a log file, which distinguishes it from siblings like head_log, tail_log, and read_log_range. The mention of 'paginated' and 'large log files' makes its purpose specific and differentiated.
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?
It explicitly says 'Useful for large log files' and mentions 'token-based pagination to respect AI context limits', providing clear guidance on when to use. However, it does not explicitly state when not to use or name alternatives, though the sibling context implies when other tools might be preferred.
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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