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dagster-mono-mcp

by pjatx
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TypeScript
Remote

dagster-mono-mcp

一个用于 Dagster 的单工具 MCP 服务器。一个工具，五个操作，极低的 Token 开销。

Dagster 有一个 官方 MCP 服务器，但我无法轻松使其运行。这是一个极简的替代方案，涵盖了您在使用 LLM 调试流水线时真正需要的操作：列出运行、检查运行详情、读取日志以及用于其他所有操作的原始 GraphQL。

支持 Cloudflare Access，适用于位于 Zero Trust 之后的 Dagster 实例——这是一种保护 Dagster 实例的简单且免费的方法。

安装

Claude Code

项目范围（在项目根目录下的 .mcp.json）：

{
  "mcpServers": {
    "dagster": {
      "command": "npx",
      "args": ["-y", "github:pjatx/dagster-mono-mcp"],
      "env": {
        "DAGSTER_GRAPHQL_URL": "https://dagster.example.com/graphql",
        "CF_ACCESS_CLIENT_ID": "your-client-id",
        "CF_ACCESS_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

全局（~/.claude.json — 在所有项目中可用）：

{
  "mcpServers": {
    "dagster": {
      "command": "npx",
      "args": ["-y", "github:pjatx/dagster-mono-mcp"],
      "env": {
        "DAGSTER_GRAPHQL_URL": "https://dagster.example.com/graphql"
      }
    }
  }
}

Cursor

添加到项目根目录下的 .cursor/mcp.json：

{
  "mcpServers": {
    "dagster": {
      "command": "npx",
      "args": ["-y", "github:pjatx/dagster-mono-mcp"],
      "env": {
        "DAGSTER_GRAPHQL_URL": "https://dagster.example.com/graphql",
        "CF_ACCESS_CLIENT_ID": "your-client-id",
        "CF_ACCESS_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

Windsurf

添加到 ~/.codeium/windsurf/mcp_config.json：

{
  "mcpServers": {
    "dagster": {
      "command": "npx",
      "args": ["-y", "github:pjatx/dagster-mono-mcp"],
      "env": {
        "DAGSTER_GRAPHQL_URL": "https://dagster.example.com/graphql",
        "CF_ACCESS_CLIENT_ID": "your-client-id",
        "CF_ACCESS_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

Related MCP server: MCP Access OAuth Server

环境变量

变量

默认值

必需

DAGSTER_GRAPHQL_URL

http://localhost:3000/graphql

否

CF_ACCESS_CLIENT_ID

—

否（如果位于 CF Access 之后则必需）

CF_ACCESS_CLIENT_SECRET

—

否（如果位于 CF Access 之后则必需）

使用方法

带有操作分发的单一工具 dagster：

列出运行

{"action": "runs"}
{"action": "runs", "status": "FAILURE"}
{"action": "runs", "job": "my_job", "limit": 5}

运行详情

{"action": "run", "id": "<run-id>"}

事件日志

{"action": "logs", "id": "<run-id>"}
{"action": "logs", "id": "<run-id>", "limit": 100}

原始 GraphQL

{"action": "graphql", "query": "{ version }"}
{"action": "graphql", "query": "query($id: ID!) { runOrError(runId: $id) { __typename } }", "variables": {"id": "abc123"}}

帮助

{"action": "help"}

返回完整文档，包括可用状态、所有参数和示例查询。

设计

本项目遵循单工具模式：一个带有操作分发的 MCP 工具，而不是许多小工具。更少的工具意味着 LLM 的 Token 开销更低，工具选择也更简单——模型不必在十几个听起来相似的工具之间进行选择。灵感来自 Cloudflare 关于重新思考 LLM 如何与 MCP 服务器交互的 Code Mode 文章。

开发

npm install
npm run build    # esbuild bundle -> dist/index.js
npm start        # run the MCP server (stdio transport)

许可证

MIT

Available Tools

1 tool
dagsterC

Dagster runs & debugging. Actions: runs, run, logs, graphql, help

{"action": "runs"} -> recent runs {"action": "runs", "status": "FAILURE"} -> failed runs {"action": "run", "id": "abc123"} -> run details {"action": "logs", "id": "abc123"} -> run logs {"action": "graphql", "query": "{ version }"} -> raw GraphQL {"action": "help"} -> full documentation

ParametersJSON Schema
NameRequiredDescriptionDefault
actionYes
idNo
jobNo
statusNo
limitNo
queryNo
variablesNo

TDQS

C2.8/5.0
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 describes what each action does (e.g., 'recent runs', 'run details'), but lacks critical behavioral traits such as authentication requirements, rate limits, error handling, or whether actions are read-only or destructive. The examples imply read operations but don't explicitly state safety.

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 a brief purpose statement followed by action examples. Each sentence earns its place by illustrating usage, though it could be more structured (e.g., bullet points) and the initial line is somewhat vague.

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 complexity (7 parameters, no output schema, no annotations), the description is incomplete. It covers actions and some parameters but misses details on return values, error cases, and full parameter semantics. Without annotations or output schema, more behavioral and contextual information is needed for effective use.

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 significant meaning beyond the input schema, which has 0% description coverage. It explains what each action does and provides example parameter combinations (e.g., 'runs' with 'status', 'run' with 'id'), clarifying how parameters interact. However, it doesn't cover all 7 parameters (e.g., 'job', 'limit', 'variables' are unexplained), so it doesn't fully compensate for the schema gap.

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 states the tool is for 'Dagster runs & debugging' and lists five actions, which gives a general purpose but lacks specificity about what Dagster is or what resources it operates on. It distinguishes between actions but doesn't clearly articulate the overall tool's function beyond listing sub-actions.

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, as there are no sibling tools mentioned. It lists actions with examples but doesn't explain prerequisites, contexts, 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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observeddagster
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.1/5.0

Scored across 1 tool

Disambiguation5/5

The single tool 'dagster' has clearly distinct actions (runs, run, logs, graphql, help) with no overlap in purpose. Each action targets a specific operation within the Dagster domain, making misselection impossible.

Naming Consistency5/5

The tool naming is perfectly consistent as there is only one tool, 'dagster', and its actions follow a clear, uniform pattern (e.g., 'runs', 'run', 'logs') without any mixing of conventions or styles.

Tool Count2/5

With only one tool, the server feels thin for a Dagster monitoring/debugging domain, as it bundles multiple distinct operations (e.g., querying runs, fetching logs, GraphQL) into a single tool. This may limit clarity and usability compared to a more granular tool set.

Completeness3/5

The tool covers core operations like retrieving runs, logs, and GraphQL queries, but lacks obvious lifecycle actions such as triggering new runs, pausing/resuming, or managing assets. This creates notable gaps for a full Dagster debugging workflow.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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