mcp-server

Call any DPF API action (fallback for requests with no dedicated tool)

call_dpf_api

Destructive

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 with a JSON body of { action, ...fields }, authenticated with your OAuth session automatically. Pass workspaceId explicitly for workspace-scoped actions (data-specs, connections, job-triggers, and under "/workspaces": get-workspace, list-queries, list-bytes-accessed, list-storage, list-processed-files, list-trigger-runs) — omit it entirely for account-level actions that reject one (under "/workspaces": create, get-workspaces, grant-permission, revoke-permission, update/delete-workspace; under "/auth/billing": get-balance only — billing mutations such as purchase-credits, modify-subscription, manage-payment, and create-customer are NOT available via MCP; direct the user to https://dpf-it.com/workspace.html#credits for all credit and subscription management). If unsure of an action's exact fields, read the "dpf-openapi-spec" resource (dpf://openapi/spec.yaml) rather than guessing. Exception: the raw Iceberg REST proxy under "/iceberg/v1/..." (e.g. to read or set a table's "dpf.primary-keys" property via a commit-table request) does not use the action convention at all — give action any placeholder string (it's ignored) and put the real Iceberg REST commit body, e.g. {"requirements":[],"updates":[{"action":"set-properties","updates":{"dpf.primary-keys":"col_a,col_b"}}]}, in params. This tool only issues POST, so Iceberg's GET-based reads (loadTable, listTables) aren't reachable this way. Returns the raw response data (or, for endpoints like the Iceberg proxy with no {success, data} envelope, the whole response body).

Input Schema

TableJSON Schema

Name	Required	Description
`path`	Yes	API path, e.g. "/auth/billing" (leading slash, no query string).
`action`	Yes	The "action" field this endpoint routes on, e.g. "get-balance".
`params`	No	Additional action-specific fields to merge into the request body alongside action/workspaceId.
`workspaceId`	No	Include for workspace-scoped actions. Omit entirely for account-level actions.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A5/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds important context beyond annotations: all requests are POST only, OAuth authentication is automatic, billing mutations are not available via MCP, and response shape varies (raw response or whole body). This enriches the destructiveHint/readOnlyHint annotations without contradicting them.

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?

Long but densely packed with necessary information–every sentence earns its place. The fallback tool's complexity justifies the length, and the text is well-structured with examples and explicit exclusions, front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, the description is remarkably complete. It covers authentication, HTTP method, workspace scoping, unsupported actions, Iceberg exception, return value conventions, and points to the OpenAPI spec for field details. The output schema exists, so return-value details are adequately supplemented.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions cover the basics, but the tool description goes much deeper: it explains path format with an example, clarifies action usage, and gives detailed guidance on workspaceId inclusion/omission. It also demonstrates how to structure params for the Iceberg proxy, adding significant semantic value beyond the schema.

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?

Clearly states it is a fallback/escape hatch for DPF API actions without a dedicated tool. The verb 'call' and resource 'DPF API action' are specific, and it explicitly contrasts with the dedicated sibling tools by saying 'ALWAYS prefer a dedicated tool when one exists'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use vs when-not-to-use guidance, naming many dedicated tools and stating to prefer them. Includes concrete examples (credits balance, new actions) and rules for workspaceId (include for workspace-scoped, omit for account-level) plus an exception for Iceberg endpoints.

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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TDQS

A4.2/5.0

Disambiguation4/5

Most tools map to distinct lifecycle phases and the descriptions explicitly separate overlapping-sounding concepts, such as list_data versus submit_query and the generic call_dpf_api from dedicated tools. The three finish_* tools are similarly worded but each is clearly tied to a specific preceding operation, so confusion should be limited.

Naming Consistency4/5

The tool names are uniformly snake_case and mostly follow a readable verb_noun pattern like delete_data_spec, create_workspace, and run_data_job. It is not a perfect 5 because broader names like manage_connection and manage_trigger, the generic call_dpf_api, and list_my_workspaces with its pronoun make the naming pattern less predictable.

Tool Count4/5

At 16 tools, the set is just slightly above the ideal range, but the tools generally earn their place by representing distinct steps or workflow boundaries. The start/finish pairs create some apparent redundancy, but that is a natural consequence of the multi-step file-upload flow.

Completeness4/5

The toolset provides solid coverage of the core data-platform lifecycle: workspaces, data specs, jobs, connections, triggers, scheduled pulls, status polling, and SQL querying. Some additional DPF capabilities are only reachable through the generic call_dpf_api rather than dedicated tools, and billing mutations are explicitly left outside the MCP surface, so coverage is strong but not absolute.

Resources

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