Atlassian Goals & Projects MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct resource and action: goal retrieval, goal update retrieval, project search, and project update retrieval. There is no overlap between goals and projects, and the update tools are clearly scoped to their respective entities.
Naming Consistency4/5All tools follow a verb_noun pattern with get_ or search_ prefixes. The compound name 'get_goal_latest_update' is slightly less elegant but still consistent with 'get_project_updates' and does not break the overall naming scheme.
Tool Count4/5With only 4 tools, the server is lean but appears well-scoped for a read-only informational purpose focused on goals and projects. No tools are redundant, and the count is reasonable for the apparent domain.
Completeness2/5The surface has significant gaps: there is no way to list or search goals, and no detailed project fetch endpoint. Users must already know a goal key to retrieve it, which creates a discovery dead end. Mutation and update operations are entirely absent, limiting the server to a narrow read-only subset.
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
- 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
- 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 for behavioral disclosure. It states what the tool returns (id, key, name, owner, archived status) and the verb 'fetch' implies a non-mutating operation, but it does not disclose error behavior, required permissions, or any side effects. For a simple read-like tool, this is adequate but not exceptional.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded with the action and resource. It avoids unnecessary detail and every word contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simply shaped tool with one parameter, no output schema, and no nested objects, the description provides sufficient context: it explains what is fetched, how to identify it, and what is returned. It does not elaborate on failure scenarios, but that is not critical for this simple fetch operation. Overall, it is complete enough for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already includes a description for the only parameter (goalKey) with an example, giving 100% schema description coverage. The tool description itself adds no additional meaning about the parameter beyond what the schema provides, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetch') and clearly identifies the resource ('an Atlassian Goal by its key'), which distinguishes it from sibling tools like get_goal_latest_update and search_projects. It also lists the returned fields, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a known Atlassian goal key, but it does not explicitly mention when not to use this tool or name alternative tools. Given that siblings exist (e.g., get_goal_latest_update), this is a missed opportunity for clearer usage 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, the description must carry the transparency burden. It discloses return fields and TQL filtering, but does not explicitly confirm read-only nature, authentication requirements, or rate limits. 'Search' implies safety, but a direct statement would be stronger.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences, three clauses, no filler. It front-loads the verb and resource, then adds return info and a usage hint, making every word valuable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with optional parameters and no output schema, the description covers the core purpose and return fields. It does not detail pagination mechanics (e.g., how 'after' works) or the behavior of an empty searchString, but the schema fills those gaps, so it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all three parameters, including examples and defaults. The description's mention of searchString adds no new semantic detail beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and the resource 'Atlassian Projects', with the parenthetical '(Townsquare)' specifying the scope. It also lists the return fields (key, name, state, pagination info), which helps distinguish it from sibling tools that focus on goals or project updates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: this tool is for searching/filtering projects. The description does not explicitly mention when not to use it or name alternative tools for different use cases. Sibling names like get_goal suggest distinctions, but the description itself lacks explicit 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 the full burden. The verb 'Fetch' implies a read-only operation, and it discloses the nature of the return content (summary + detailed notes). However, it does not disclose behaviors like what happens if no update exists, error conditions, or response structure. This is adequate but not rich, so a 3 is suitable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that immediately conveys the tool's purpose and content. It includes no filler or redundancy, and the parenthetical (summary + detailed notes) adds value without unnecessary length. This is concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input (one goal key) and no output schema, the description provides a high-level overview of the return content. However, it does not specify the exact structure of the response (e.g., whether it's a single object, includes timestamps, etc.). It is sufficient for basic use but leaves some ambiguity about the return shape, so a 4 is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'goalKey' is fully described in the schema (100% coverage), so the description does not need to add much. The description does not provide extra parameter information, but the schema already explains the format with an example. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the specific resource 'latest status update' for an Atlassian Goal, including the content (summary + detailed notes). This distinguishes it from sibling tools like get_goal (which would fetch the goal itself) and get_project_updates (which operates at the project level). The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes it clear this tool is for retrieving a specific goal's latest update, which is sufficient context for when to use it. It does not explicitly exclude uses or mention alternatives, but the context is clear enough that an agent would not confuse it with the sibling tools. A 4 is appropriate because it provides clear context without formal exclusions.
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 discloses the read-only nature ('Fetch') and enumerates the returned content (highlights, Jira items, notes), but it does not mention permissions, rate limits, pagination, or error behavior. For a read operation this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is front-loaded with the verb 'Fetch' and lists the key output components. Every word adds value; there is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple tool with three required parameters and no output schema. The description lists the output components, which helps an agent understand what to expect. It could mention the response format (e.g., array) or limitations, but it is largely complete for this basic fetch operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters. The description adds context by saying 'one or more' and 'within a date range', but it does not provide additional syntax or format details beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Fetch' and clearly identifies the resource: detailed updates, highlights (decisions/learnings/risks), linked Jira items, and update notes for Atlassian Projects. This distinguishes it from sibling tools like get_goal (goals) and search_projects (project search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this to fetch updates for one or more projects within a date range. It does not explicitly state when not to use it or name alternatives, but the scope is unambiguous enough to guide selection among siblings.
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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