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Langflow

Langflow is an open-source low-code visual builder for AI agents, RAG pipelines, and LangChain-based workflows. It pairs a drag-and-drop React Flow frontend with a FastAPI backend that exposes every flow as a REST API, an MCP server, and an OpenAI-compatible Responses endpoint. Components are editable Python and ship with integrations across most major LLMs, vector stores, and observability platforms. Langflow was acquired by DataStax in 2025; DataStax itself was acquired by IBM and the deal closed on May 28, 2025, making Langflow an IBM property while remaining MIT-licensed open source. The project is the canonical reference implementation for visually composing LangChain agents — 149k+ GitHub stars, distributed via PyPI, Docker, Helm, and native Desktop apps, with a hosted cloud option run by DataStax.

agent ready

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.

Kin Score

API Evangelist profiles Langflow the way a machine reads it — 55 machine-readable artifacts across 15 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 — Langflow scores 47.6/100 (developing), with a separate agent-readiness read of 48/100 (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.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 47.6/100 · developing
Contract Quality 17.7 / 25
Developer Ergonomics 9.6 / 20
Commercial Clarity 0.0 / 20
Operational Transparency 2.7 / 13
Governance 8.8 / 12
Discoverability 8.8 / 10
Agent readiness — 48/100 · agent ready
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
MCP Server 0 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 7 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile Langflow

Each block below is one kind of artifact we hold for Langflow. 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 15

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.

Langflow Base API

The Base API from Langflow — 6 operation(s) for base.

Langflow Chat API

The Chat API from Langflow — 6 operation(s) for chat.

Langflow Files API

The Files API from Langflow — 11 operation(s) for files.

Langflow Flow Events API

The Flow Events API from Langflow — 1 operation(s) for flow events.

Langflow Flows API

The Flows API from Langflow — 8 operation(s) for flows.

Langflow Health Check API

The Health Check API from Langflow — 2 operation(s) for health check.

Langflow Log API

The Log API from Langflow — 2 operation(s) for log.

Langflow MCP API

The MCP API from Langflow — 2 operation(s) for mcp.

Langflow mcp_projects API

The mcp_projects API from Langflow — 4 operation(s) for mcp_projects.

Langflow Monitor API

The Monitor API from Langflow — 12 operation(s) for monitor.

Langflow OpenAI Responses API API

The OpenAI Responses API API from Langflow — 1 operation(s) for openai responses api.

Langflow Projects API

The Projects API from Langflow — 4 operation(s) for projects.

Langflow Traces API

The Traces API from Langflow — 2 operation(s) for traces.

Langflow Users API

The Users API from Langflow — 4 operation(s) for users.

Langflow Workflow API

The Workflow API from Langflow — 2 operation(s) for workflow.

Scroll within the panel for all 15 ·

Open Collections 1

Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

Langflow

OPEN COLLECTION

Features 22

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.

Visual drag-and-drop builder for AI agents, RAG pipelines, and LangChain workflows
FastAPI-based REST API with OpenAPI 3.1 spec served at /docs and /openapi.json on every deployment
67 REST endpoints covering flows, builds, projects, files, users, API keys, MCP servers, monitoring, and traces
OpenAI-compatible Responses endpoint (/api/v1/responses) so OpenAI clients can target a Langflow flow
Webhook execution endpoint per flow for event-driven invocation
Streaming flow execution via SSE on the build endpoints
Native MCP (Model Context Protocol) server — every Langflow project is exposable as an MCP server
MCP client support for consuming external MCP servers as Langflow components
Project / flow / component hierarchy with import-export, batch operations, and public-flow sharing
Session-aware chat with shared sessions for read-only collaboration
Built-in trace explorer plus integrations with LangSmith and LangFuse for observability
Pluggable Python components — every component's source is editable in the UI
Multi-agent orchestration with conditional routing and tool calls
Vector-store integrations including Astra DB, Chroma, Pinecone, Milvus, Weaviate, Qdrant, and pgvector
LLM integrations including OpenAI, Anthropic, Google, Azure, Bedrock, Mistral, Cohere, Hugging Face, Ollama, and Groq
File upload and per-user file management with batch operations (v2 Files API)
API key authentication via `x-api-key` header or query parameter
Auto-login mode for local dev and superuser mode for production
Distributed by Python package on PyPI (`pip install langflow`), Docker image (`langflowai/langflow:latest`), Helm chart, and Desktop app for macOS and Windows
MIT-licensed, written in Python (FastAPI backend) and TypeScript (React Flow frontend)
149k+ GitHub stars, v1.9.3 (May 2026) — actively maintained by langflow-ai with 800+ contributors
Hosted Langflow Cloud offering operated by IBM DataStax (post-acquisition)

Scroll within the panel for all 22 ·

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.

Langflow Context

27 classes · 13 properties

JSON-LD

Spectral Rules 2

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.

Langflow API Rules

5 rules · 4 warnings

SPECTRAL

Langflow API Rules

6 rules · 3 warnings

SPECTRAL

JSON Schema 5

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.

FlowRead

19 properties

JSON SCHEMA

MCPServerConfig

5 properties

JSON SCHEMA

MessageResponse

15 properties

JSON SCHEMA

FolderReadWithFlows

6 properties

JSON SCHEMA

UserRead

10 properties

JSON SCHEMA

JSON Structure 1

JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.

JSON Structure definitions describing this provider's data shapes.

Langflow Flow Structure

10 properties

JSON STRUCTURE

Examples 4

Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.

Example request and response payloads for these APIs.

Security 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.

Langflow Authentication

apiKey/oauth2 · 3 schemes

SECURITY

Langflow Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Scopes 1

OAuth scopes are the vocabulary of least-privilege access. Profiling them shows exactly what an integration — or an agent acting on a user's behalf — is allowed to do.

OAuth scopes governing access to this provider's APIs.

Langflow Scopes

OAuth 2.0 · no documented scopes

0 scopes

SCOPES

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.

Langflow Agentic Access

95 operations · 53 acting · 2 human-in-the-loop

95 operations · 53 acting

AGENTIC

Resources

Every other property we hold for Langflow — 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

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Learn 1

Tutorials, courses, talks, and written guidance

Commercial 1

Pricing, plans, and the legal terms of use

Other 4

Properties that don't map to a standard resource type

← All providers · Data indexed from github.com/api-evangelist/langflow · machine-readable index on apis.io