influx-timeseries-mcp
A selective, aggregation-first MCP server for InfluxDB v2 that bounds output and pushes reduction to the database, avoiding context flooding from raw time-series data.
README
influx-timeseries-mcp
A selective, aggregation-first Model Context Protocol (MCP) server for InfluxDB v2 (Flux), built for LLM use where flooding the context window with raw time-series points is the failure mode to avoid.
Status: in development. Design spec:
docs/superpowers/specs/2026-06-12-influx-timeseries-mcp-design.md
Why
Generic InfluxDB MCP servers expose "run arbitrary Flux → return all rows." For time-series and event data that dumps tens of thousands of points into the model on a single query. This server inverts that: every path pushes reduction to InfluxDB and bounds its output, so the database returns kilobytes and the model stays focused.
Design
- Aggregation-first. All windowing, grouping, percentiles, and limits are expressed in the Flux sent to InfluxDB — the server never pulls raw series into memory to reduce them.
- Hybrid tool surface. Cheap discovery tools (measurements, tags, fields) +
curated selective queries (
aggregate,top_n,count_events,latest) + a guarded raw-Flux escape hatch (mandatory range, auto-injected limit, byte-capped response). - Bounded by construction. Range is mandatory; results are double-capped (max rows AND max bytes); truncation is explicit, never a silent partial dump.
- Read-only. No write/admin tools; runs with a read-only InfluxDB token.
Runtime
Python + the MCP SDK (FastMCP), run as a stdio server. Packaged as a container for the homelab MCP gateway.
License
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