API-driven analyst conversations
Create chats against connected data sources with POST /chats, then send questions the same way you would in the Basedash app.
Basedash developer platform
RevendiquerBasedash developer platform exposes AI analyst, dashboards, insights, and automations via API and MCP server for embedded analytics and BI workflows.
Overview
Basedash developer platform turns Basedash’s internal analytics product into an API and agent-accessible infrastructure layer. Instead of using the app only through its UI, teams can create chats, stream answers, render charts, and manage dashboards, automations, and data sources from their own code.
The platform is intended for two main workflows: building customer-facing analytics inside a product, and wiring Basedash into internal tools and automation systems. The launch post frames it as a way to avoid rebuilding query layers, charting, permissions, and multi-tenant isolation from scratch while still keeping the analyst, dashboards, and insights backed by Basedash.
Core capabilities
Streaming responses and progress updates
Receive analyst work as server-sent events, including schema exploration, SQL generation and verification, chart creation, and the final answer.
Chart rendering and export
Render structured chart objects through an image endpoint or use the objects directly in your own UI, emails, or PDF reports.
Programmatic control of the platform
Manage dashboards, dashboards tabs, insights, automations, runs, data sources, metric definitions, members, groups, audit logs, and AI usage from code.
Agent access through MCP
Use the Basedash MCP server with agents such as Claude Code, Cursor, and ChatGPT to query data and receive verified answers.
Multi-tenant data scoping
Scope queries with row-level security so customer-specific data stays isolated across embedded or custom analytics experiences.
Common use cases
Customer-facing analytics
Embed analytics inside a customer product with Basedash handling question answering, query generation, and chart creation behind your UI.
Automated internal workflows
Trigger analysis from another system, then send the result into a support workflow, internal app, status page, or other operational surface.
Reporting and chart distribution
Render dashboards and chart images into emails, PDFs, wikis, and internal tools when you need reports outside the Basedash app.
Agent-assisted data access
Use the MCP server with coding or agent tools to ask data questions and receive verified answers without building a separate conversation layer.
Infrastructure-style BI operations
Manage dashboards, automations, data sources, and audit logs as code when you want Basedash to fit into existing infrastructure and governance processes.
Pros and Cons
Pros
- Exposes the same analyst, insights, automations, and dashboards that Basedash uses internally through an API.
- Supports streamed answers, structured chart objects, and chart image output for use in custom interfaces and reports.
- Includes multi-tenant scoping with server-side row-level security for customer-facing analytics.
- Can be used both outwardly for embedded or custom product analytics and inwardly for internal BI workflows and automated reporting.
- Pricing is published with a flat-rate Startup plan, a free trial, and an enterprise path for larger deployments.
Cons
- Advanced deployment needs such as self-hosting, SSO, SCIM, and audit logs are described on the pricing page as enterprise features, not part of the Startup plan.
- The source does not provide a full public specification for every integration, security control, or API endpoint, so some implementation details need to be confirmed in the API reference.
FAQ
How do you get started with the developer platform?
Yes. The API is available to all Basedash workspaces, and getting started begins by signing up or logging in, connecting a data source, creating an API key in Settings → API keys, and making a POST /chats request with a question about your data.
What is the platform for?
The API is meant for teams that want to use Basedash capabilities in their own product or internal systems. The launch post specifically calls out customer-facing analytics, internal BI workflows, chart rendering in apps or reports, and agent-driven data access through the MCP server.
What kind of output does the API provide?
The API returns streamed analyst responses, status updates, SQL execution details, chart objects, and final answers. Chart responses also include an image endpoint, so results can be rendered in custom components or exported into emails and PDF reports.
How is Basedash priced?
Basedash pricing is flat-rate rather than per-seat on the Startup plan. The pricing page says the Startup plan is $1,000/month plus AI usage for up to 25 users, with a 14-day free trial and custom Enterprise plans for larger deployments.
Can Basedash be deployed in enterprise environments?
The pricing page says self-hosting is available for teams that need tighter network control or stricter compliance requirements. It also mentions enterprise options such as SSO, SCIM, audit logs, custom AI models, and deployment in VPC-based environments.
Quick Facts
- Category
- Developer tool / AI analytics platform
- Platform
- API and web app
- Primary use
- Customer-facing analytics and internal BI workflows
- Pricing shape
- Flat-rate Startup plan plus AI usage; custom Enterprise plans
- Trial
- 14-day free trial
- Domain
- basedash.com
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