mcp-server

{
  "id": "aix_c3bfdb66fd",
  "name": "mcp-server",
  "operator": "(unclaimed - source: registry-official · publisher: com.dpf-it)",
  "description": "AI-powered data integration platform. Onboard users and run DPF data workflows.",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-24",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "object-storage"
  ],
  "protocols": {
    "mcp": "https://api.dpf-it.com/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 2922,
    "uptime_30d": 1,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 42,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-24T21:00:37.073Z"
  },
  "pricing_model": "unknown",
  "profile": {
    "mcp_server": "dpf-mcp-remote",
    "mcp_version": "1.0.0",
    "tool_count": 18,
    "tools": [
      {
        "name": "list_my_workspaces",
        "description": "List every workspace the authenticated user has access to, including their permission on each."
      },
      {
        "name": "create_workspace",
        "description": "Create a new workspace, owned by the authenticated user. Use this if list_my_workspaces returns none."
      },
      {
        "name": "list_data",
        "description": "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 paginated (default 25/page, max 100, newest first); pass the returned nextCursor to fetch more.\n\nThis is NOT a table listing — specs describe configured pipelines (parsing/mapping rules), not the live set of Iceberg tables in the workspace. Multiple specs can target the same table (e.g. one spec creates it, another merges "
      },
      {
        "name": "get_status",
        "description": "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/update-spec + start-analysis, poll by specId; once that reaches \"ready\", its response's lastJobId (if present) points at the data-load job — poll that separately by jobId for load progress."
      },
      {
        "name": "delete_data_spec",
        "description": "Permanently delete a data spec and its associated configuration."
      },
      {
        "name": "submit_query",
        "description": "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 (catalog/schema prefixes, e.g. information_schema.tables) are rejected; reference tables by name only. Table functions that introspect the engine itself (e.g. duckdb_functions(), duckdb_tables()) are also rejected as external-data-source access — don't try to discover available SQL functions this way. A BLOB column is very"
      },
      {
        "name": "manage_connection",
        "description": "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 using this connection) will succeed. For aws_s3, create generates an ExternalId and returns a trustPolicy plus dpfPrincipalArn — the customer must create (or update) the IAM role at roleArn with that trust policy and a permissions policy granting the S3 access DPF needs, before test will succeed. Either type must pass t"
      },
      {
        "name": "manage_trigger",
        "description": "Create, list, update, delete, or fire a workspace job trigger. Four types:\n- \"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's type; aws_s3 also requires s3Bucket (s3Prefix optional). Natural-language preRules (which files to pick up) and postRules (what to do after upload) are compiled into executable code server-side — never pass raw code. The connection must already exist and have passed test (see manage_connection). For a first-time \"se"
      },
      {
        "name": "onboard_data_source",
        "description": "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) — upload the file(s) per the returned instructions, then call finish_data_source_onboarding with the returned specId to kick off AI analysis and wait for it to complete.\n\nUse sourceType \"tables\" instead when the request is to derive/aggregate data that is ALREADY loaded into workspace tables — e.g. \"build me a daily summary of the customers table\", or \"set up a job that reads from the orders table "
      },
      {
        "name": "finish_data_source_onboarding",
        "description": "Call after uploading the file(s) returned by onboard_data_source — kicks off AI analysis and waits until the spec reaches \"ready\" or \"failed\". If it returns before that (timedOut: true), do NOT call this tool again just to keep checking — that re-attempts starting analysis. Poll with get_status (specId) instead until it reaches a terminal status."
      },
      {
        "name": "update_data_spec",
        "description": "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 given, this instead returns presigned upload URL(s); upload the file(s), then call finish_data_spec_update. Only pass the fields you want to change — omitted fields keep their current value."
      },
      {
        "name": "finish_data_spec_update",
        "description": "Call after uploading the file(s) returned by update_data_spec — kicks off AI analysis and waits until the spec reaches \"ready\" or \"failed\". If it returns before that (timedOut: true), do NOT call this tool again just to keep checking — that re-attempts starting analysis. Poll with get_status (specId) instead until it reaches a terminal status."
      },
      {
        "name": "run_data_job",
        "description": "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 it to complete.\n\nDo NOT call this right after onboard_data_source/finish_data_source_onboarding or update_data_spec/finish_data_spec_update unless loadSampleData was explicitly set to false there — by default those already load and process the sample file as their own job (see the returned lastJobId), so calling run_dat"
      },
      {
        "name": "finish_data_job",
        "description": "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) instead until it reaches a terminal status."
      },
      {
        "name": "setup_scheduled_pull",
        "description": "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 that feeds an already-analyzed data spec (see onboard_data_source) on the given frequency. Pass hostname for an sftp pull, or roleArn (+ s3Bucket, required) for an aws_s3 pull — exactly one of the two is expected. Use this instead of calling manage_connection + manage_trigger yourself for first-time setup. If the connec"
      },
      {
        "name": "call_dpf_api",
        "description": "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_pull, list_my_workspaces, create_workspace — and reach for this only when none of those fit (e.g. \"how many credits do I have?\" -> path \"/auth/billing\", action \"get-balance\"; a brand-new action added to the API since this server's tools were last updated). Every DPF endpoint is POST <path> with a JSON body of { action,"
      },
      {
        "name": "manage_account",
        "description": "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 every action instead returns the DPF website's own form, or a curl command that reads the password from a shell variable the user sets themselves in their own terminal. Hand the command to the user to run — do not run it yourself even if you have shell access, since composing the export line would require seeing the pass"
      },
      {
        "name": "contact",
        "description": "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."
      }
    ],
    "profiled_at": "2026-09-24T21:00:37.073Z"
  },
  "unreachable": false,
  "payment_method": "auth"
}