MCP and SDK Now Available

Give your AI agents
instant knowledge.

One API to ingest, embed, and query documents. Usage-based pricing. Sub-150ms retrieval.

import { Orchata } from '@orchata-ai/sdk';
// Create your Orchata client
const client = new Orchata({
apiKey: 'oai_your_api_key'
});
// Query your knowledge base
const { results } = await client.query({
spaceIds: 'space_123',
query: 'How do I reset my password?'
});
console.log(results[0].chunk.content);

Ingest Anything

PDFs, docs, markdown, HTML, images and more. We handle chunking and embedding.

Fast By Default

P50 retrieval under 150ms. Optimized vector search at scale.

Pay for what you use

No vector database or infra to manage. Simple usage-based pricing.

How it works

From documents to answers in three steps.

01

Upload your documents

Drop in PDFs, markdown, HTML, or plain text. Use our SDK, API, dashboard, or let your AI handle it via our MCP server.

PDFproduct-guide.pdf
02

We handle the rest

Automatic chunking, embedding generation, and vector indexing. No infrastructure to manage.

chunking
embedding
indexing
Animated BeamAnimated BeamAnimated Beam
03

Query from anywhere

Use our TypeScript SDK, REST API, or MCP server. Get results in milliseconds.

Query
"How do I set up auth?"
0 results0ms
0.94
0.89
0.85
Features

Everything you need.

Nothing you don't.

Multi-tenant

Isolated knowledge spaces for every use case.

Create separate spaces for different projects, clients, or data sources. Each space has its own documents, embeddings, and query scope. Search one space or query across all of them.

  • Complete data isolation between spaces
  • Per-space usage analytics
  • Granular access control with API keys

Product Documentation

API references, guides, and SDK documentation for developers

Customer Support

Knowledge base articles, FAQs, and troubleshooting guides

Legal & Compliance

Terms of service, privacy policies, and compliance docs

Sales Enablement

Pitch decks, case studies, and competitive analysis

Performance

Built for speed, not just accuracy.

We obsess over latency. Our retrieval is optimized for real-time applications – chatbots, copilots, and agents that can't afford to wait. P50 under 150ms.

  • Sub-150ms P50 query latency
  • Optimized embedding models
  • Scales without degradation
147ms

Average query latency

0ms150ms300ms
Integration

Native MCP support for AI agents.

Connect any MCP-compatible assistant to your knowledge base. Claude Desktop, Cursor, Windsurf, and other agents can query your docs directly. No custom integration code.

  • Works with Claude Desktop
  • Cursor and Windsurf ready
  • Any MCP-compatible client
JSON
1{
2 "mcpServers": {
3 "orchata": {
4 "name": "Orchata",
5 "url": "api.orchata.ai/mcp"
6 }
7 }
8}
Developer Experience

SDKs that don't suck. TypeScript-first.

Fully typed SDK with autocomplete that actually helps. Upload documents, manage spaces, and query your knowledge base in a few lines. We handle retries, errors, and edge cases.

  • Full TypeScript definitions
  • Async/await native
  • Automatic retries and error handling
TypeScript
1import { Orchata } from '@orchata-ai/sdk';
2
3const client = new Orchata({
4 apiKey: 'oai_your_api_key'
5});
6
7const { space } = await client.spaces.create({
8 name: 'Documentation',
9 description: 'Product documentation and guides',
10 icon: 'book'
11});
12
13const { document } = await client.documents.uploadFile({
14 spaceId: 'space_123',
15 file: fileInput.files[0]
16});
17
18const { results } = await client.query({
19 spaceIds: 'space_123',
20 query: 'How do I reset my password?'
21});

Ready to give your AI
instant knowledge?

Start free. Pay only for what you use.