DPF
DPF is an AI‑powered data processing platform offering zero‑ETL transformation to Apache Iceberg. It enables users to ingest, transform, and load data in open formats via natural‑language prompts, provides a built‑in query engine, and supports bring‑your‑own‑compute integrations for collaborative data workflows.
Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.
API Evangelist profiles DPF the way a machine reads it — 27 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — DPF scores 47.0/100 (developing), with a separate agent-readiness read of 50/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.
Kin Score
How this is scored →scored 2026-11-06 · rubric v0.27.0
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How we profile DPF
Each block below is one kind of artifact we hold for DPF. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 11
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
DPF Account API
Account management endpoints (password reset, etc.)
DPF Authentication API
User authentication and registration endpoints
DPF Connections API
Workspace external connections (e.g. SFTP) with managed keypairs
DPF Contact API
Contact form endpoint with two modes: authenticated (user info auto-populated from account) and unauthenticated (email required in request body). No authentication required to s...
DPF Data Specs API
Data transformation pipeline management and orchestration
DPF Iceberg REST Catalog API
Apache Iceberg REST Catalog proxy with JWT authentication and workspace-scoped namespace access control. Provides standard Iceberg REST Catalog API access to your Iceberg tables.
DPF Job Triggers API
Scheduled ingestion triggers (e.g. SFTP polling) with AI-generated pre/post-processing code
DPF MCP API
Remote Streamable HTTP MCP (Model Context Protocol) server. A single JSON-RPC endpoint, authenticated with a Bearer token from either the OAuth 2.1 Authorization Server (recomme...
DPF OAuth 2.1 Authorization Server API
PKCE-only OAuth 2.1 authorization server with Dynamic Client Registration (DCR) and refresh token rotation. Used by remote MCP clients (VS Code, Cursor, Claude, ChatGPT) to obta...
DPF Query API
DuckDB-powered SQL query interface for executing analytical queries against Iceberg tables. Queries are scoped to a single authorized namespace per request.
DPF Workspaces API
Workspace management and collaboration endpoints
Scroll within the panel for all 11 ·
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
Agent Skills 3
An agent skill packages the how-to for driving these APIs from an assistant — the prompts, the sequence, the guardrails — so the knowledge to use the API travels with it.
Packaged agent skills for driving this provider's APIs from an AI assistant.
dpf-it-com-create-and-load-iceberg-table
AGENT SKILLdpf-it-com-execute-query
AGENT SKILLdpf-it-com-obtain-access-token
AGENT SKILLPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the things the Kin Score reads for access clarity — renamed from commercial clarity in rubric 0.12, because a free statutory interface has access terms and no commercial ones.
Published pricing tiers and plan structures.
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Dpf It Com Context
JSON-LDSpectral Rules 1
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
DPF API Rules
SPECTRALJSON Schema 6
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
Check Spec Files Response
JSON SCHEMACreate Spec
JSON SCHEMAGet Status Response (queried by jobId)
JSON SCHEMAGet Status Response (queried by specId)
JSON SCHEMAQueryResponse
JSON SCHEMAUpdate Spec
JSON SCHEMASecurity Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Resources
Every other property we hold for DPF — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 5
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 6
Pagination, idempotency, versioning, errors, and events
Access & Security 2
Authentication, authorization, and security posture
Commercial 4
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Other 2
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/dpf-it-com · machine-readable index on apis.io
This is an independent, third-party profile of DPF, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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