mcp-openproject-standalone

Server Quality Checklist

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Latest release: v1.0.3
Disambiguation5/5
Each tool targets a distinct resource and action: projects have list/get, work packages have list/get/create/update, statuses have list and available transitions, and comments have add. There's no overlap that would confuse an agent.
Naming Consistency5/5
All tools follow the verb_noun pattern consistently: list_*, get_*, create_*, update_*, add_*. All names are lowercase snake_case, and the verbs clearly indicate the operation.
Tool Count5/5
The 9 tools are well-scoped for the OpenProject domain, covering projects, work packages, statuses, and comments without excessive fragmentation or missing essentials.
Completeness4/5
Core work package lifecycle is covered (create, read, update), and status workflows are well supported. Missing delete operations and project creation are minor gaps that don't severely impact typical usage.
Average 3.7/5 across 9 of 9 tools scored. Lowest: 2.4/5.
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
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This repository is licensed under MIT License.
This repository includes a README.md file.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden but only states 'Create', which is inherent to the tool name. It does not disclose side effects, required permissions, return behavior, or any other operational characteristics beyond the obvious mutation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and concise, but it is under-specification rather than efficient communication. It merely restates the tool's purpose with no additional value, so it does not 'earn its place' beyond the name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters and no output schema, but the description provides no behavioral or operational context. For a mutation tool with zero annotations, it is severely incomplete — it lacks information about what happens after creation, required permissions, or any side effects.
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 the baseline is 3. The description adds no extra meaning beyond the schema; it does not elaborate on any parameters, but the schema already provides complete field descriptions, so no deduction is warranted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource ('Create a new work package in a project') which clearly distinguishes it from siblings like list_work_packages, get_work_package, and update_work_package. It unambiguously states the tool's creation purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 update_work_package or get_work_package. The description gives no contextual cues about prerequisites, typical use cases, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It implies a write operation ('Add') but does not mention prerequisites, side effects, or response behavior—important 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 a single, front-loaded sentence with zero unnecessary words. It is concise and directly states the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should compensate by explaining return values or side effects, but it only provides the most basic action. It also lacks context about prerequisites (e.g., work package must exist) and what happens after the comment is added.
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?
The input schema already provides complete descriptions for both parameters (work_package_id and comment), so the description adds no additional parameter semantics. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Add' with the resource 'comment' and the target 'work package', making its function immediately clear. It distinguishes itself from sibling tools like create_work_package and update_work_package.
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 does not explicitly state when to use this tool versus alternatives, but the tool name and the sibling list make the intended use (adding a comment to a work package) reasonably obvious. No explicit exclusions or alternative references are provided.
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 burden of behavioral disclosure. 'List all available statuses' implies a read-only operation with no side effects, but it does not describe pagination, response structure, or any access constraints. This is acceptable for a simple list tool but lacks depth.
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, front-loaded sentence with no redundant information. It is concise and easy to parse.
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?
For a zero-parameter, list-style tool, the description is sufficient to inform the agent of its purpose and scope. There is no output schema, but the return value (a list of statuses) is implicit. The description is appropriately complete given the tool's simplicity.
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 accepts zero parameters, so there are no parameter semantics to explain. The description correctly makes no mention of parameters, and the input schema confirms that none are required.
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 the resource ('statuses'), scoped to 'all available' within OpenProject. However, it does not differentiate from the sibling tool 'get_available_statuses', which appears to perform a similar operation.
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 list_statuses versus get_available_statuses or other tools. It does not mention any preconditions, typical scenarios, or exclusions, leaving the agent to infer usage from the name alone.
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. It only states the obvious (retrieves a project) and does not disclose return format, possible errors (e.g., 404), or any side effects. For a read operation, it adds minimal behavioral context beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no waste. It is front-loaded with the action and resource, and every word contributes to meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description provides a minimal but adequate explanation. However, it leaves gaps: it does not specify what 'details' includes or what happens if the project is not found. For a getter, this is passable but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the only parameter (project_id as 'The ID of the project'), with 100% schema coverage. The description adds no extra meaning beyond what the schema provides, so the 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 uses a specific verb ('Get') and resource ('project'), and clearly scopes it to 'a specific project by ID'. This distinguishes it from sibling tools like list_projects, which would retrieve multiple projects.
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 phrase 'by ID' clearly indicates when to use this tool (when you have a specific project ID), but it does not explicitly mention alternatives or when not to use it, such as pointing to list_projects for all projects.
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 burden of behavioral disclosure. The verb 'Get' implies a read-only operation, which is useful, but the description does not elaborate on return format, error behavior, or whether the details include nested related resources. It is not contradictory, but adds minimal context beyond the verb itself.
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, clear sentence of nine words that front-loads the action and resource. Every word is meaningful, with no redundant phrasing or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-by-ID operation with one parameter and straightforward schema, the description is adequate. However, since there are no annotations and no output schema, a bit more context about return shape or behavior on missing IDs would improve completeness. Still, the tool's simplicity keeps it close to 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 coverage is 100%: the work_package_id parameter is described as 'The ID of the work package'. The tool description adds only 'by ID', which restates the schema. Thus the schema does the heavy lifting, and the description adds no additional semantic value beyond the parameter explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with a clear resource ('work package') and identifies the scope ('specific', 'by ID'). This inherently distinguishes it from sibling tools like list_work_packages (which retrieves multiple) and create/update_work_package.
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 when you have a work package ID and need its details, but it does not explicitly state when NOT to use this tool or mention alternatives like list_work_packages for browsing. The context is clear from 'by ID', but no explicit guidance is provided.
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?
Since no annotations are provided, the description carries the burden. It discloses that it returns current status and all settable statuses, indicating a read-only operation, but it does not mention error handling, authorization needs, or any edge cases. It adds some context ('workflow') but lacks deeper behavioral details.
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 two sentences, front-loaded with the main purpose, and every clause adds value. It is concise and well-structured.
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 simplicity (one parameter, no output schema, no annotations), the description adequately covers what the tool does and what it returns. It does not explain return format, but that is acceptable for a simple getter.
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% (work_package_id is clearly described as 'The ID of the work package'). The description adds minimal parameter-specific meaning beyond mentioning 'specific work package', so the baseline of 3 applies.
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 a specific verb ('Get') and resource ('available status transitions for a specific work package'), and differentiates from siblings by focusing on a specific work package and workflow context. It also explains the return value in a distinct way.
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 conveys clear usage context: when you need status transitions for a specific work package. It does not explicitly mention alternatives or exclusions, but the context is sufficient to distinguish it from list_statuses and other sibling 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?
With no annotations, the description must convey behavioral traits. 'List all work packages' clearly implies a read-only operation and the scope is specified. However, it doesn't disclose potential details like pagination, ordering, or permission requirements, which are not critical for a simple list but could be relevant.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that immediately states the action, resource, and scope without any filler or unnecessary detail. Every word 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?
For a simple tool with one parameter and no output schema, the description is nearly complete. It tells the user what to expect (a list of work packages for a project), though it doesn't mention the return format or pagination. Still, the essential context is present.
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 a clear description for project_id. The tool description merely restates the parameter by saying 'given project', adding no additional meaning beyond what the schema already provides. 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 action 'List' and the resource 'work packages' with a scope ('in a given project'), which distinguishes it from siblings like get_work_package (single item) and list_projects (different resource). It is specific 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied (use when you need all work packages for a project), but there is no explicit guidance on when to use this versus get_work_package or when not to. The description provides context but lacks alternative suggestions or exclusion criteria.
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 alone must disclose behavior. It notes that only 'visible' projects are returned, implying permission-based filtering, which is useful. However, it does not mention pagination, whether archived projects are included, or the response structure, leaving behavioral gaps for a list 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, front-loaded sentence that states exactly what the tool does without redundancy. Every word 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?
The tool is simple: no parameters, no output schema, and the description clearly states the tool's purpose. It does not describe the return format, but given the low complexity and the broad scope of 'visible projects', this is an adequate level of completeness for an AI agent to select the tool correctly.
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, so the schema is fully covered (100%) and there is no param semantic burden. The baseline for no-param tools is 4, and the description does not need to add parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and a clear resource 'all visible OpenProject projects'. It distinguishes itself from sibling tools like get_project (which fetches a single project) and list_work_packages (which lists a different resource type).
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 phrase 'all visible OpenProject projects' clearly conveys the context: use this tool to enumerate all projects the user can see. There is no explicit statement about when not to use it or alternatives, but the scope is clear enough for typical list scenarios.
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 must disclose behavioral traits itself. It does this by explaining that status transitions are validated automatically, using a concrete example of an invalid jump, and stating that an error will be returned with available statuses. This goes beyond the schema and gives the agent critical expectations for error handling. It doesn't cover all possible side effects, but the key behavior is well disclosed.
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 three sentences: the first states the action, the second explains the validation behavior with a specific example, and the third points to a sibling tool for valid transitions. It is front-loaded, every sentence earns its place, and there is no redundant wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an update tool with no output schema and no annotations, the description covers the core functionality, the critical validation rule, error behavior, and a reference to a relevant sibling tool. It doesn't mention return values, but that is often implicit for updates, and the lock_version requirement is already in the schema. The description is sufficiently complete for an agent to invoke the tool correctly, though it could potentially mention optimistic locking implications.
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?
The input schema already provides descriptive comments for all five parameters, covering 100% of them. The description adds a general note about status validation but does not materially expand on the schema's per-parameter semantics. Baseline 3 is appropriate when the schema does the heavy lifting, and the description adds minimal extra value.
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 opens with 'Update an existing work package,' which clearly specifies the verb (update) and resource (work package) and distinguishes it from sibling tools like create_work_package, get_work_package, and list_work_packages. No ambiguity remains about what this tool does.
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 (updating existing work packages) and explicitly instructs using get_available_statuses to see valid transitions, which is a direct reference to an alternative for a subtask. It doesn't explicitly exclude create or list operations, but the purpose statement already differentiates. The guidance is sufficient, though not exhaustive.
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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