Chaprola
Expose a serverless Chaprola HTTP backend—queries, joins, pivot, batch jobs, email, FHIR, and programs—to your agent without standing up custom infra first.
Overview
Chaprola is an MCP server for the Build phase that connects agents to a serverless Chaprola API backend for query, join, pivot, batch, email, FHIR, and program operations.
What is this MCP server?
- npm package @chaprola/mcp-server 1.4.3 with stdio MCP transport
- Serverless API: query, JOIN, pivot, batch operations, email, FHIR, and programs over HTTP
- Requires CHAPROLA_USERNAME and CHAPROLA_API_KEY (chp_ plus 64 hex chars) from https://api.chaprola.org/register
- Repository subfolder mcp-server on GitHub cletcher/chaprola-mcp
- Lets agents orchestrate backend data work without you writing every HTTP client call by hand
- Server metadata version 1.4.3
- npm identifier @chaprola/mcp-server
- Two required environment variables: CHAPROLA_USERNAME and CHAPROLA_API_KEY
What problem does it solve?
Solo builders need SQL-like and batch backend power fast but do not want to craft and maintain a large HTTP integration surface for every agent task.
Who is it for?
Builders validating data-heavy MVPs or agent workflows that fit Chaprola’s hosted API model, including FHIR-oriented experiments.
Skip if: Teams that require exclusively on-prem databases, or anyone unwilling to register and store a Chaprola API key for agent access.
What do I get? / Deliverables
Once username and API key are set, your agent can call Chaprola backend capabilities through MCP tools instead of bespoke scripts per operation.
- Agent-driven queries, joins, pivots, and batch actions against Chaprola
- Email and program invocation paths exposed through MCP tools
- Faster backend iteration without hand-written HTTP glue for each endpoint
Recommended MCP Servers
Journey fit
You adopt Chaprola while building data-backed features and APIs, before operating production SRE playbooks or growth funnels. Backend is canonical because the server models a programmable API surface (SQL-like ops, batch, FHIR) rather than front-end polish or launch SEO.
How it compares
Hosted serverless API MCP, not a raw Postgres MCP or Clerk docs remote.
Common Questions / FAQ
Who is Chaprola MCP for?
Solo developers and small teams using AI agents to drive a Chaprola serverless backend for queries, transforms, batch jobs, and related HTTP programs.
When should I use Chaprola MCP?
Use it in build while prototyping backend features, pivots, and batch flows before you harden ship-stage security and production monitoring.
How do I add Chaprola MCP to my agent?
Register at https://api.chaprola.org/register, set CHAPROLA_USERNAME and CHAPROLA_API_KEY, install npm @chaprola/mcp-server, and configure stdio MCP in your host.