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Topk

TopK is a search engine for accuracy-critical AI applications, delivering hybrid search, multi-vector (late-interaction) retrieval, dense and sparse vector search, BM25 keyword search, custom ranking, document parsing, and grounded question answering through a single API. Built on object storage for roughly 10x lower cost and effectively unlimited scale, TopK exposes a Collection API for structured document storage and querying, a Dataset API for unstructured document ingestion, semantic search, and evidence-backed answers, and a Management API for datasets and collections. It ships official Python, JavaScript, Rust, and SQL (PostgreSQL-wire) SDKs, a Homebrew-installable CLI, and a hosted MCP server so AI agents can query private data with natural language. TopK is developed by topk-io and is a portfolio company of Earlybird.

agent aware

Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.

Kin Score

API Evangelist profiles Topk the way a machine reads it — 8 machine-readable artifacts across 3 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 — Topk scores 43.5/100 (thin), with a separate agent-readiness read of 33/100 (agent aware). 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 — 43.5/100 · thin
Contract Quality 0.0 / 25
Developer Ergonomics 15.2 / 20
Commercial Clarity 12.1 / 20
Operational Transparency 6.2 / 13
Governance 0.0 / 12
Discoverability 10.0 / 10
Agent readiness — 33/100 · agent aware
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 5 / 5
Well-Known Catalog 4 / 4
Consent & Bot Identity 3 / 3

How we profile Topk

Each block below is one kind of artifact we hold for Topk. 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 3

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.

TopK Collection API

Structured document store and query surface. Create collections with typed, indexed fields (keyword_index, semantic_index, vector index), upsert/update/delete documents by `_id`...

TopK Dataset API

Unstructured document ingestion, semantic search, and grounded question answering. Upload document files (PDF, Markdown, HTML, and more) to a dataset, retrieve the most relevant...

TopK Management API

Create, list, get, update, and delete datasets and collections that back TopK search and retrieval.

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.

topk-mcp.yml

MCP SERVER

Security Posture 4

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.

Topk Authentication

http · 1 scheme

SECURITY

Topk Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Topk Vulnerability Disclosure

security.txt · contact published

SECURITY

Topk Trust Center

SOC 2

SECURITY

Resources

Every other property we hold for Topk — 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 4

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Build 4

SDKs, sample code, and the tooling you integrate with

Operate 2

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/topk · machine-readable index on apis.io