GigAPI
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.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/gigapi/gigapi-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve GigAPI from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.