com.dpf-it/mcp-server

up checked 2026-11-11T00:37:57.665Z

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Publisher-provided description

AI-powered data integration platform. Onboard users and run DPF data workflows.

Summary by lookupd

Onboards data sources, runs file processing jobs, manages SFTP/S3 connections and schedules, and runs SQL queries on workspace tables.

Install

Claude Code, remote (streamable-http)

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

Codex, remote (streamable-http)

codex mcp add server --url https://api.dpf-it.com/mcp

Cursor, remote (streamable-http) → .cursor/mcp.json

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

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (18 tools)

Publisher-provided text

• 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 wo
• 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
• 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 aut
• 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 keyp
• 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 buc
• 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 (a
• 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
• 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
• 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 sp
• 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 fil
• 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: t
• 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 workspa
• 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, de
• manage_account Returns instructions for creating a DPF account, verifying its email, resending the verification code, or resetting a forgotten password — it never performs the
• 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

Details

• Version: 1.0.0
• Transports: streamable-http
• Uptime (7 days): 100%
• Median latency: 466 ms
• First indexed: 2026-11-01T08:53:46.184Z
• Last seen in registry: 2026-11-01T08:53:46.232Z

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