Dpf It MCP

安装

选择你使用的 AI 应用，然后复制设置。

通过 2/3 项检查 · 你的提问会经过开发者的服务器（api.dpf-it.com）

claude mcp add --transport http --scope user dpf-it https://api.dpf-it.com/mcp

{
  "mcpServers": {
    "dpf-it": {
      "url": "https://api.dpf-it.com/mcp"
    }
  }
}

{
  "servers": {
    "dpf-it": {
      "type": "http",
      "url": "https://api.dpf-it.com/mcp"
    }
  }
}

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

通过互联网连接，适用于

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

全部应用及其优缺点 →

它能做什么

工具名称和描述与服务器在 2026年11月10日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• list_my_workspaces

  List every workspace the authenticated user has access to, including their permission on each.

• create_workspace

  Create a new workspace, owned by the authenticated user. Use this if list_my_workspaces returns none.

• list_data

  List either the data specs (parsing + mapping rule sets, resource: "specs") or the data processing jobs (executions of a spec, resource: "jobs") defined in a workspace. Each spec includes its specId and current status — poll a specific one with get_status. Both resources are pagi

• get_status

  Poll the status of either a data spec's own process (schema inference + code generation, run by start-analysis — pass specId, reaches "ready" or "failed") or a data-load job (pass jobId, reaches "complete" or "failed"). Pass exactly one of specId or jobId. Right after create-spec

• delete_data_spec

  Permanently delete a data spec and its associated configuration.

• submit_query

  Run a SQL query against the Iceberg tables loaded into a workspace. To list the tables that actually exist in the workspace, run `SHOW TABLES` — this is the authoritative source (unlike list_data's specs, which describe pipelines, not live tables). Qualified table references (cat

• manage_connection

  Create, list, test, or delete a workspace connection to an external data source. Two types are supported: "sftp" and "aws_s3". For sftp, create generates a keypair and returns the public key — it must be installed in the remote server's authorized_keys before test (or a trigger u

• manage_trigger

  Create, list, update, delete, or fire a workspace job trigger. Four types: - "sftp"/"aws_s3": pulls files from a connection (sftp: remote server; aws_s3: S3 bucket/prefix) into an already-analyzed data spec on a schedule (hourly/daily/monthly, UTC). Type must match the connection

• onboard_data_source

  First step of setting up a new data integration: creates a data spec. By default (sourceType "file") this returns presigned upload URL(s) for the sample file (and optional format/target-schema file). Creating the spec does NOT upload anything: you must PUT each file to its URL yo

• finish_data_source_onboarding

  Call ONLY after the file(s) returned by onboard_data_source have actually been uploaded (each PUT returned HTTP 200) — kicks off AI analysis and waits until the spec reaches "ready" or "failed". This tool verifies the upload against storage before starting anything. If a file is

• update_data_spec

  Change an existing data spec's configuration. If no replacement file names are given, this runs synchronously (no upload needed): saves changes and — by default — re-runs AI analysis, returning the final status directly. If a replacement sample/format/target-schema file name IS g

• finish_data_spec_update

  Call ONLY after the file(s) returned by update_data_spec have actually been uploaded (each PUT returned HTTP 200) — kicks off AI analysis and waits until the spec reaches "ready" or "failed". The upload is verified against storage first: if a file is missing this refuses, spends

• run_data_job

  First step of processing new data files through an already-configured data spec: creates a job and returns presigned upload URL(s) for each file. Upload the file(s) per the returned instructions, then call finish_data_job with the returned jobId to start processing and wait for i

• finish_data_job

  Call after uploading the file(s) returned by run_data_job — starts processing and waits until the job completes or fails. If it returns before that (timedOut: true), do NOT call this tool again just to keep checking — that re-attempts starting the job. Poll with get_status (jobId

• setup_scheduled_pull

  End-to-end workflow for "pull files from this SFTP server / S3 bucket on a schedule" requests: reuses a matching connection if one already exists in the workspace (same hostname/username for sftp, same roleArn for aws_s3), otherwise creates one; tests it; then creates a trigger t

• call_dpf_api

  Escape hatch for DPF capabilities that don't have a dedicated tool yet. ALWAYS prefer a dedicated tool when one exists — get_status, list_data, submit_query, delete_data_spec, onboard_data_source, update_data_spec, run_data_job, manage_connection, manage_trigger, setup_scheduled_

• manage_account

  Returns instructions for creating a DPF account, verifying its email, resending the verification code, or resetting a forgotten password — it never performs these itself and never asks for a password. A password typed into this chat would sit in the conversation transcript, so ev

• contact

  Send a message to the DPF team — request a demo, ask about licensing, report an issue, or request a feature. No authentication required. Always ask the user for their email if they have not already given it in this conversation.

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月13日

• ! 注意

  作者与仓库一致

  注册中心没有列出源代码仓库，因此无法将发布者（dpf-it.com）与代码对应起来

• … 尚未检查

  仍在维护

  我们还没有从 GitHub 读取这个仓库

• … 尚未检查

  有许可证

  我们还没有从 GitHub 读取这个仓库

• ✓ 通过

  端点有响应

  在 149 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 18 个工具描述，未发现针对 AI 的隐藏指令

用户评价

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与“其他”中的其他服务器比较i

• 星标数多于此分类中其他 19420 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 19420 个服务器的 15% 更新
• 基础检查结果等于或优于此分类中其他 19420 个服务器的 44%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

同类别的其他选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 104 tools.

作者：koala73·广泛使用·★ 9.1万·昨天更新

在云端运行✓ 服务方 · worldmonitor.app

接入方法

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

作者：ruvnet·广泛使用·↓ 1.4万/周·★ 8.2万·14个月前更新

在你的电脑上运行

安装

Windmill

Run Windmill scripts and flows and manage jobs, schedules, resources and variables.

作者：windmill-labs·广泛使用·★ 1.9万·昨天更新

在云端运行

接入方法

作者的 README

仓库中没有找到 README