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Open-source analytics agent builder for context engineering

Site Internet :https://getnao.io/
Ajouté :13 juil. 2026
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open sourceanalytics agentscontext engineeringdata analyticsself-hostedMCP
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Informations sur l’outil

Qu'est-ce que nao ?

nao is an open-source analytics agent builder for context engineering that lets teams build, evaluate, and deploy reliable analytics agents on their own data stack. It enables users to engineer agent context like a file system, synchronize data and metadata sources, measure reliability with tests, and deploy natural-language analytics chat agents that can be self-hosted or connected via MCP.

Fonctionnalités principales

  • Context file-system engineering

    Create and organize agent context as a file system, adding data, metadata, rules, docs, tools, and MCPs without hard limits.

  • Context synchronization

    Automatically pull and sync context from databases, repositories, and external sources such as Notion.

  • Context reliability testing

    Run unit tests of questions-to-SQL and obtain metrics on context reliability, answer rate, time, and token usage.

  • Deployable chat UI

    Deploy a chat interface so anyone can ask plain-English questions about data and create data stories while monitoring chats.

  • Bring your own key (BYOK)

    Deploy chat with your own LLM key and pay only for token consumption.

  • Multi-channel access via MCP

    Ask questions from Slack, Teams, WhatsApp, Telegram, Claude, Codex, Cursor, or anywhere with nao MCP.

  • Self-hosting

    Self-host the analytics agent with your own LLM keys so data stays in your infrastructure under your control.

  • Context Engineering playbook

    Guidance on optimizing agent context for reliability, structure, and modularity.

Cas d'utilisation

  • #1

    Build reliable analytics agents

    Engineer structured context from warehouse schemas, metrics, models, docs, and rules to create dependable analytics agents.

  • #2

    Natural-language data analytics

    Let users ask questions about data in plain English through a chat UI or integrated channels.

  • #3

    Measure and improve agent reliability

    Create tests for questions-to-SQL and monitor pass rates, answer rates, latency, and token usage.

  • #4

    Secure self-hosted analytics

    Run the agent and LLM keys inside your own infrastructure for maximum data control.

  • #5

    Team-wide analytics access

    Deploy a chat UI or MCP connections so non-technical users can run analytics on shared data context.

Idéal pour :Data teamsAnalytics engineersData analystsOrganizations building internal analytics agents

Plans tarifaires

Described as 100% open source. Users can self-host and bring their own LLM key, paying only for token consumption. Pricing and Services pages are linked but detailed plans are not specified in the provided snapshots.

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Foire aux questions

What is nao?
nao is an open-source analytics agent builder for context engineering that lets teams build, evaluate, and deploy reliable analytics agents on their own data stack.
Is nao open source?
Yes. It is described as 100% open source. Users can self-host and bring their own LLM key, paying only for token consumption.
Can I self-host nao?
Yes. You can self-host the analytics agent with your own LLM keys so data stays in your infrastructure under your control.
How does context engineering work in nao?
You create and organize agent context as a file system, adding data, metadata, rules, docs, tools, and MCPs without hard limits, and can automatically sync from databases, repositories, and external sources such as Notion.
Where can users ask questions with nao?
Through a deployable chat UI or via MCP from Slack, Teams, WhatsApp, Telegram, Claude, Codex, Cursor, or other supported channels.
How can I measure agent reliability?
Create unit tests of questions-to-SQL and obtain metrics on context reliability, answer rate, time, and token usage.

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Informations sur l’outil

Modèle tarifaireOpen Source
CatégorieAnalyse de données
Tags
open sourceanalytics agentscontext engineeringdata analyticsself-hostedMCP
LangueAnglais
Dernière mise à jour16 juil. 2026
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