Jira 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, create_issue, get_issue, and update_issue handle different lifecycle stages, while get_my_issues and search_issues serve different query needs. The descriptions reinforce these distinctions, making tool selection unambiguous.
Naming Consistency5/5
All tools follow a consistent verb_noun naming pattern (e.g., add_comment, create_issue, get_issue). There are no deviations in style or convention, making the set predictable and easy to parse for an agent.
Tool Count5/5
With 8 tools, this server is well-scoped for Jira operations, covering core workflows like issue management and project queries. Each tool serves a clear purpose without bloat, aligning with typical server sizes of 3-15 tools.
Completeness4/5
The toolset provides strong coverage for Jira's core domain, including CRUD operations for issues and basic project management. A minor gap exists in missing tools for deleting issues or managing comments beyond addition, but agents can work around this with available tools.
Average 3.3/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No high-severity vulnerability alerts
- No code scanning findings
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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 full burden but only states it 'creates a new Jira issue'. It lacks details on permissions needed, whether creation is idempotent, error handling, or rate limits. This is inadequate for a mutation tool with zero annotation coverage.
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 front-loaded with the purpose, followed by a structured parameter list. It's efficient with minimal waste, though the parameter explanations could be slightly more detailed without losing conciseness.
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 6 parameters, no annotations, and an output schema (which reduces need to explain returns), the description is moderately complete. It covers parameters but lacks behavioral context and usage guidelines, making it adequate but with clear gaps for a creation 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%, but the description compensates by listing all 6 parameters with brief explanations (e.g., 'project_key: The project key (e.g., 'PROJ')'). It adds meaning beyond the schema's titles, though it could provide more context like format constraints or examples for enums.
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 creates a new Jira issue, specifying the verb 'Create' and resource 'Jira issue'. It distinguishes from siblings like 'update_issue' or 'get_issue' by focusing on creation, though it doesn't explicitly mention sibling differentiation.
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 like 'update_issue' or 'add_comment' is provided. The description lists parameters but doesn't indicate prerequisites, context, or exclusions for usage.
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. It states the tool retrieves issues but lacks details on permissions required, whether it's read-only or has side effects, pagination behavior beyond max_results, or error handling. For a tool with no annotation coverage, this is a significant gap in transparency.
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 appropriately sized and front-loaded, with the core purpose stated first followed by parameter details. Every sentence adds value, and there's no redundant information. It could be slightly more structured with bullet points, but it's efficient and clear.
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 moderate complexity (2 parameters, no annotations, but with an output schema), the description is adequate but incomplete. It covers the purpose and parameters well, but lacks behavioral context like permissions or side effects. The presence of an output schema means return values don't need explanation, but other gaps remain.
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. The schema has 0% description coverage, but the description explains that 'status' filters by status with examples ('To Do', 'In Progress', 'Done') and that 'max_results' sets a maximum with a default of 10. This compensates well for the low schema coverage, though it doesn't cover all possible parameter nuances.
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's purpose: 'Get issues assigned to the current user.' It specifies the verb ('Get') and resource ('issues assigned to the current user'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_issue' (which likely gets a specific issue) or 'search_issues' (which might allow broader filtering), so it falls short of a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_issues' or 'get_issue', nor does it specify prerequisites or contexts for usage. The only implied usage is filtering issues by status and limiting results, but this is parameter information, not usage guidance.
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 states this is a read operation ('Get'), which implies it's non-destructive, but doesn't mention authentication requirements, rate limits, error conditions, or what 'detailed information' includes. This leaves significant gaps for a tool that likely interacts with a project management system.
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 appropriately concise with two sentences: one stating the purpose and another explaining the parameter with an example. It's front-loaded with the core functionality. The structure is clean, though the 'Args:' formatting could be slightly more polished.
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 handles return values), the description's main gaps are in usage guidelines and behavioral transparency. For a simple read tool with one parameter, the description is minimally adequate but lacks context about when to use it versus siblings and operational constraints.
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 for the single parameter 'project_key' by providing an example format ('e.g., "PROJ"'), which is valuable since schema description coverage is 0%. This compensates well for the lack of schema descriptions, though it doesn't explain where to find project keys or validation rules.
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's purpose with a specific verb ('Get') and resource ('detailed information about a specific project'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_projects' or 'get_issue', which would be needed for a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives like 'list_projects' (for listing all projects) or 'get_issue' (for issue details). It mentions the required parameter but doesn't explain the context or prerequisites for using this specific retrieval tool.
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 the full burden of behavioral disclosure. It states the action is to 'add' a comment, implying a write operation, but doesn't cover critical aspects like authentication requirements, permission levels, rate limits, error conditions, or whether the comment is editable after creation. This is a significant gap 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 efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence adds value without redundancy, and it's front-loaded with the core functionality. The brevity is appropriate for this straightforward tool.
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 moderate complexity (2 parameters, mutation operation) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks behavioral details (e.g., side effects, error handling) and usage guidelines, making it incomplete for safe and effective agent use without additional 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 schema, which has 0% description coverage. It clarifies that 'issue_key' follows a specific format (e.g., 'PROJ-123') and that 'comment' is text to add, providing practical usage hints. However, it doesn't detail constraints like comment length or special characters, leaving some ambiguity.
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 action ('Add a comment') and target resource ('to a Jira issue'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'update_issue' which might also allow comment modifications, leaving room for ambiguity in tool selection.
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 doesn't mention prerequisites (e.g., needing issue access), compare it to similar tools like 'update_issue', or specify use cases (e.g., for adding feedback versus updating status). This leaves the agent without contextual decision-making support.
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. While 'List all accessible' implies a read-only operation that returns multiple items, it doesn't specify format, pagination, sorting, authentication requirements, rate limits, or what 'accessible' means in practice. The description provides minimal behavioral context beyond the basic 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 a single, efficient sentence that states exactly what the tool does without any wasted words. It's appropriately sized for a simple list operation with no parameters, and the information is front-loaded with the core functionality.
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?
For a zero-parameter list tool with an output schema, the description covers the basic operation adequately. However, with no annotations and important behavioral aspects (like what 'accessible' means, pagination, format) left unspecified, there are gaps that could hinder optimal tool selection and invocation despite the output schema handling return values.
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 tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't waste space discussing non-existent parameters, earning a baseline score of 4 for not introducing confusion about parameters that don't exist.
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 action ('List') and resource ('Jira projects'), with the qualifier 'accessible' providing useful scope information. However, it doesn't specifically differentiate this from sibling tools like 'get_project_info' which might retrieve details about a specific project rather than listing all projects.
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?
The description provides no guidance about when to use this tool versus alternatives like 'get_project_info' or 'search_issues'. There's no mention of prerequisites, timing considerations, or comparison with sibling tools that might also retrieve project information in different ways.
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 but lacks critical behavioral details. It states this is an update operation (implying mutation) but doesn't disclose permission requirements, whether changes are reversible, rate limits, or what happens when fields are omitted (defaults vs. no change). The presence of an output schema helps, but the description itself is minimal on behavior.
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 well-structured with a brief purpose statement followed by a bullet-like parameter list. Every sentence earns its place by explaining parameters, though it could be more front-loaded with key behavioral context. 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?
Given 5 parameters with 0% schema coverage and no annotations, the description does well on parameters but lacks behavioral context for a mutation tool. The output schema exists, so return values needn't be explained, but completeness is moderate due to missing usage guidelines and transparency details.
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?
Schema description coverage is 0%, so the description must compensate fully. It provides clear semantics for all 5 parameters: 'issue_key' with an example, 'status' with examples, 'assignee' with usage notes, 'priority' with enum values, and 'summary' with clarification. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Update') and resource ('an existing Jira issue'), making the purpose unambiguous. It distinguishes from siblings like 'create_issue' (creates new) and 'get_issue' (reads), though it doesn't explicitly contrast with all siblings like 'add_comment'.
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 is provided. The description doesn't mention prerequisites (e.g., issue must exist), exclusions (e.g., cannot update certain fields), or comparisons to siblings like 'add_comment' for adding comments instead of updating issue fields.
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. It states the tool retrieves 'detailed information,' which hints at a read-only operation, but doesn't clarify aspects like authentication requirements, rate limits, error handling, or what 'detailed information' entails. This leaves gaps in understanding the tool's behavior beyond its basic purpose.
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 in the first sentence, followed by a concise parameter explanation. Every sentence adds value without redundancy, making it efficient and easy to parse for an 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 (1 parameter, no nested objects) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the purpose and parameter semantics adequately, though it could benefit from more behavioral details like error cases or performance hints to fully guide the 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 description adds meaningful context for the single parameter 'issue_key' by explaining it's 'The issue key (e.g., 'PROJ-123'),' which clarifies the expected format and provides an example. Since schema description coverage is 0% (the schema only lists the parameter without description), this compensates well, though it doesn't cover edge cases or validation rules.
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's purpose: 'Get detailed information about a specific Jira issue.' It specifies the verb ('Get') and resource ('Jira issue'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_my_issues' or 'search_issues', which also retrieve issue information but with different scopes or filters.
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 by specifying it's for 'a specific Jira issue,' suggesting it should be used when you have an exact issue key. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_my_issues' (for user-specific issues) or 'search_issues' (for broader queries), leaving some ambiguity for the agent in selecting the right tool.
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 the full burden of behavioral disclosure. It mentions the tool searches but doesn't describe key behaviors such as pagination (implied by max_results), authentication needs, rate limits, error handling, or whether it's read-only (though searching is typically safe). This leaves significant gaps for an agent to understand operational constraints.
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 well-structured with a brief overview followed by a clear parameter list. Every sentence earns its place by providing essential information, though it could be slightly more front-loaded with key usage notes. There's no wasted text, making it efficient for an agent 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 moderate complexity (7 parameters, no annotations, but with an output schema), the description is partially complete. It excels in parameter semantics but lacks behavioral context (e.g., safety, limits). The presence of an output schema means return values don't need explanation, but other operational aspects are underspecified, leaving room for improvement.
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 substantial meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose with examples (e.g., 'currentUser()' for assignee, status names like 'To Do'), clarifies that jql is for advanced searches, and notes max_results has a default of 20. This fully compensates for the lack of schema descriptions.
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 for Jira issues using JQL or simple filters, which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_my_issues' or 'get_issue', which might also retrieve issues but with different scopes or methods.
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 by mentioning 'JQL or simple filters' and listing filter parameters, suggesting it's for flexible searching. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_my_issues' (for user-specific issues) or 'get_issue' (for a single issue by ID), 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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