Power Query
Power Query is a data transformation and mashup engine used across Microsoft products including Excel, Power BI, and Azure. This API collection provides programmatic access to Power Query functionality for data connectivity, transformation, and integration using the M formula language and connector SDK.
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 Power Query the way a machine reads it — 27 machine-readable artifacts across 6 APIs, 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 — Power Query scores 45.3/100 (developing), with a separate agent-readiness read of 7/100 (human only). 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.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Power Query
Each block below is one kind of artifact we hold for Power Query. 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 6
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.
Power Query REST API
REST API for executing Power Query mashups and managing data transformations programmatically.
Power Query M Formula Language
API and language reference for the M formula language used in Power Query for data transformation expressions and custom functions.
Power Query Connectors API
API for building and managing custom data connectors for Power Query using the M language and Connector SDK.
Power Query Dataflows API
API for managing and executing Power Query dataflows in Power Platform and Power BI for self-service ETL workflows.
Power Query SDK
Development toolkit for building custom Power Query connectors using Visual Studio Code, including project scaffolding, testing, and packaging of .mez connector files.
Fabric Power Query Programmatic API
REST API for programmatically executing Power Query M transformations in Microsoft Fabric, enabling integration with Spark notebooks, pipelines, and external applications.
Pricing 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 six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Power Query Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Power Query Finops
FINOPSFeatures 6
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Data Transformation Engine
Powerful M formula language for complex data transformations including filtering, pivoting, merging, and custom functions.
Custom Connector Development
Build custom data connectors using the Power Query SDK for connecting to any data source.
Self-Service ETL
Dataflows provide self-service ETL capabilities for business users without IT dependency.
300+ Built-In Connectors
Pre-built connectors for databases, cloud services, files, and web APIs.
Incremental Refresh
Efficient data loading with incremental refresh policies for large datasets.
Microsoft Fabric Integration
Execute Power Query transformations programmatically in Microsoft Fabric pipelines.
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.
Power Query Context
JSON-LDSecurity Posture 1
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.
Use Cases 5
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Data Preparation
Clean, transform, and shape data from multiple sources for analytics and reporting.
Custom Data Connectors
Build reusable connectors for proprietary or specialized data sources.
Automated Data Pipelines
Create scheduled dataflows for automated data refresh and transformation workflows.
Cross-Platform Data Integration
Integrate data across Power BI, Excel, Azure Data Factory, and Microsoft Fabric.
Data Quality Management
Implement data quality rules and transformations for consistent enterprise data.
Integrations 5
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Power BI
Native integration with Power BI for data preparation and visualization workflows.
Microsoft Excel
Built-in Power Query editor in Excel for spreadsheet-based data transformation.
Azure Data Factory
Mapping data flows using Power Query transformations in Azure Data Factory.
Microsoft Fabric
Programmatic execution of Power Query in Fabric notebooks and pipelines.
SQL Server
Direct connectivity and query folding optimization for SQL Server databases.
Resources
Every other property we hold for Power Query — 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.
Get Started 3
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 4
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/power-query · machine-readable index on apis.io