mcp-dagster

by kyryl-opens-ml

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Server Quality Checklist

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Latest release: v0.1.2
Disambiguation5/5
Each tool targets a distinct resource and action: listing repositories, jobs, assets; getting run/asset info; and actions like launch/terminate/materialize. There is no ambiguity between tools.
Naming Consistency4/5
Most tools follow a verb_noun pattern (list_*, get_*, launch_run, terminate_run, materialize_asset), but 'recent_runs' breaks the pattern as an adjective-noun phrase. This is a minor deviation.
Tool Count5/5
9 tools is well-scoped for a Dagster server covering repositories, jobs, assets, and runs. It provides necessary operations without being excessive.
Completeness4/5
The surface covers listing and getting info for key entities, plus launching/terminating runs and materializing assets. A minor gap is the lack of get_job_info or more granular run listing, but core workflows are supported.
Average 3/5 across 9 of 9 tools scored. Lowest: 2/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on April 9, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
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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```
{
  "$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?
No annotations are provided, and the description gives no information about side effects, required permissions, return values, or whether materialization triggers a background run. The single sentence offers no behavioral disclosure beyond the name, so the agent cannot anticipate the tool's impact.
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 a single concise sentence with no filler or repetition. It is well-structured as a simple statement, though the brevity comes at the expense of necessary detail.
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?
Given zero annotations, zero parameter descriptions, no output schema, and a non-trivial operation, the one-line description is grossly incomplete. It lacks any explanation of how parameters are used, what 'materialize' means in Dagster, or how it relates to sibling tools, making it inadequate for correct tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions for asset_key, repository_name, or repository_location (0% coverage), and the description does not mention any parameter. The agent is left without guidance on how to populate values or what each parameter represents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Materialize a specific Dagster asset' names the action and resource but adds little beyond the tool name. It does not clarify what materialization entails or distinguish it from sibling tools like launch_run, making it only slightly more specific than a tautology.
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 given for when to use this tool versus alternatives such as launch_run, list_assets, or get_asset_info. The description neither states prerequisites nor excludes other tools, leaving the agent without decision criteria.
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 must carry the full burden. It only says 'Launch' without disclosing side effects, permissions, run behavior (e.g., immediate vs queued), or error handling. This is insufficient for a mutation-like operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), but it omits critical information necessary for correct usage. While concise, it is not appropriately sized given the tool's complexity.
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?
Given the lack of annotations, output schema, and parameter descriptions, the one-sentence description is insufficient for a tool with 4 parameters and a run configuration input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the tool description does not compensate by explaining any of the parameters (repository_location, repository_name, job_name, run_config). Users cannot infer parameter semantics from the description.
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 ('Launch') and the resource ('a Dagster job run'), which distinguishes it from sibling tools like list_repositories or terminate_run. However, it lacks additional context about the launch process or specific job 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 like materialize_asset or terminate_run. It does not mention prerequisites, such as needing a valid repository location/name or when to use run_config.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It does not state that this is a read-only operation, what 'recent' means (e.g., time window), whether results are ordered, or if failed runs are included. No behavioral details beyond the obvious are given.
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 a single, front-loaded sentence with no filler. It is appropriately concise for a simple tool, though it sacrifices depth for brevity.
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?
Given no output schema and no annotations, the description is incomplete. It does not specify the structure of the returned runs, the definition of 'recent', or any potential side effects. It works as a basic label but not as a complete tool guide.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the 'limit' parameter or its effect. The schema only provides the type and default, leaving the agent without any guidance on how the limit influences the result set.
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 uses the specific verb 'Get' and the resource 'recent Dagster runs', making the core function clear. It does not explicitly distinguish from siblings like get_run_info, but the plural 'runs' and 'recent' imply a list operation distinct from single-run details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as get_run_info or list_jobs. There is no mention of prerequisites, appropriate contexts, or exclusions—only a bare statement of functionality.
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 explaining behavior. It only states that detailed information is returned, but does not disclose whether this is a read-only operation (though obvious from 'get'), any error conditions, or what constitutes 'detailed'. This is minimal behavioral disclosure.
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, short sentence that is easy to parse and front-loads the core purpose. It contains no superfluous information.
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?
Given there is no output schema, the description should explain what 'detailed information' includes or how the response is structured. It does not, and with only one parameter and no annotations, the context remains incomplete for an agent to anticipate the tool's output or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the 'run_id' parameter. While the parameter name is self-evident, the description adds no extra context about its format, required syntax, or how it is used. For a low-coverage schema, the description does not compensate.
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 ('get') and the resource ('detailed information about a specific run'), making it distinct from sibling list tools like 'recent_runs' and 'list_jobs'. However, it does not explicitly mention that it operates based on a run_id, making it slightly less precise than a 5.
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 offers no guidance on when to use this tool versus alternatives. It does not say 'use this when you need details for one run' or 'use list_* to find runs first', leaving the agent to infer usage entirely.
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 implies a read-only operation ('get') but does not disclose any behavior such as error handling, return format, or what constitutes 'detailed information'. The description adds minimal transparency beyond the basic action.
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 is front-loaded with the action and resource. Every word contributes to the meaning, with no unnecessary filler.
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 lacks an output schema, yet the description does not describe what information is returned. It only says 'detailed information', which is vague and incomplete for an agent attempting to use the tool effectively. No error cases or expected behavior are mentioned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 for the parameter 'asset_key'. It does not explain the format, allowed values, or how to obtain a valid key. The parameter name is somewhat self-explanatory, but no additional semantics are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get detailed information about a specific asset.' It uses a specific verb (get), a resource (asset), and a scope (specific asset), which distinguishes it from the sibling tool 'list_assets' that lists assets generally.
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 does not mention exclusions or when to prefer this over 'list_assets' or 'get_run_info'. The usage context is only implied by the tool's name and purpose.
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. It only says 'List all jobs' without disclosing any additional behavioral traits such as read-only nature, pagination, ordering, return format, or required permissions. The description adds no context beyond what the tool name already implies.
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 is front-loaded with the action and resource. Every word earns its place, and there is zero redundancy.
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 is simple, but with no output schema and no annotations, the description should at least indicate what 'jobs' are and what the list returns (e.g., job IDs, names, statuses). It does not provide enough contextual detail for an agent to fully understand the tool's behavior or result structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 for the params. It mentions 'in a specific repository' but does not explain what 'repository_location' or 'repository_name' mean (e.g., URL, path, identifier). The parameter names are somewhat self-explanatory but lack crucial detail about the expected values.
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 'List all jobs in a specific repository' uses a specific verb ('list') and resource ('jobs') with a clear scope ('specific repository'). This clearly distinguishes it from siblings like list_repositories and list_assets, which target different resources.
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 only implies that a repository must be specified, but it does not explicitly state when to use this tool versus alternatives or provide prerequisites (e.g., 'Use list_repositories to find repository names'). There are no exclusions or alternative tool references.
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 must disclose behavior. It only says 'list all assets,' which implies a read-only operation, but it does not explain return format, pagination, or potential side effects. 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 that conveys the core purpose without unnecessary detail. It is appropriately sized for a simple list operation.
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 tool is simple with two parameters and no output schema. The description gives the basic scope, but it lacks details on expected output or parameter usage. It is minimally viable but leaves the agent uncertain about how to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two required parameters with no descriptions (0% coverage), and the description only mentions 'specific repository' without explaining the meaning or relationship of repository_location and repository_name. The description fails to compensate for the missing schema 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 clearly states the tool lists assets within a specific repository, using a specific verb and resource. This distinguishes it from sibling tools like list_repositories and list_jobs, which target different resource types.
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 the user needs to enumerate assets in a repository, but it does not explicitly state when to prefer this tool over alternatives like get_asset_info or materialize_asset. There is no exclusion or alternative 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 full burden. It implies a read-only operation and 'all available' adds scope, but it does not disclose return format, authentication needs, or potential side effects. The behavior is minimally disclosed but not richly 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?
A single, clear sentence that is front-loaded and uses no unnecessary words. 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 list tool with no params and no output schema, the description is adequate as it states exactly what it does. It clearly identifies the resource and scope, making it complete enough for its simplicity, though it could mention return structure if desired.
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, and the description correctly doesn't mention any. Per the baseline for 0 parameters, this is sufficient and no semantic additions are needed.
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 'List' and resource 'repositories', and clarifies 'all available Dagster' which distinguishes it from sibling tools like list_jobs and list_assets. It clearly communicates the exact scope and domain.
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 does not mention any prerequisites, exclusions, or alternative tools, so usage context is entirely absent.
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 states that the operation targets 'in-progress' runs, but does not disclose side effects such as whether termination is immediate, whether partial outputs are discarded, or whether special permissions are required. This is minimal 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 sentence with no extraneous words, delivering the essential information immediately. It is perfectly sized for the tool's simplicity.
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 is sufficiently complete for its core use case, noting the constraint that the run must be in-progress. It lacks edge-case details, but for a straightforward terminate action, it is adequate.
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 schema provides a single required 'run_id' parameter with 0% description coverage, and the tool description does not mention the parameter. However, the parameter's purpose is inherently clear from its title 'Run Id' and the tool name 'terminate_run', so an agent can infer its meaning without additional description.
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 'Terminate' and identifies the resource as 'an in-progress Dagster run', which clearly distinguishes it from sibling tools like 'launch_run' (starting) and 'recent_runs' (listing). This is unambiguous and immediately actionable.
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 'in-progress' provides clear context for when this tool is applicable, implicitly indicating it should be used only for currently running runs, not queued or completed ones. However, it does not explicitly name alternatives or exclusions, but the constraint is strong enough for effective selection.
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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