# GigAPI

> Use this tool when you need to integrate time-series data management with AI workflows, enabling seamless execution of SQL queries, database management, and data ingestion. It solves problems related to time-series analytics, IoT data processing, and real-time monitoring by providing a robust interface for managing databases and tables. With inputs via InfluxDB Line Protocol and outputs in NDJSON format, it's ideal for AI assistants working with large-scale time-series data.

Canonical page: https://skillsregistry.net/skills/gigapi-timeseries  
JSON: https://api.skillsregistry.net/v1/skills/gigapi-timeseries

## Description

This MCP server provides seamless integration with GigAPI Timeseries Lake, enabling AI assistants to execute SQL queries, manage databases and tables, and write time-series data using InfluxDB Line Protocol. Built by the GigAPI team with Python and leveraging GigAPI's HTTP API with NDJSON response format, it offers tools for database operations including health checks, schema inspection, and data ingestion. The implementation supports both local development and production deployments with authentication, SSL configuration, and connection to public demo instances, making it particularly useful for AI assistants working with time-series analytics, IoT data processing, and real-time monitoring applications.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/gigapi-timeseries)
- **Repository:** <https://github.com/gigapi/gigapi-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "gigapi-timeseries"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gigapi-timeseries` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gigapi-timeseries/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt