Loading…
Offline market diagnostics, news repetition, data coverage and statistical checks for AI agents.
NoiseFloor — market attention and evidence checks is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 78/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding NoiseFloor — market attention and evidence checks to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
mcp add io.github.beepboop2025/noisefloor https://api.seiche.info/noisefloor/mcpReview the upstream source before running this command.
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-10-18T00:05:38.416044Z",
"publishedAt": "2026-10-18T00:05:38.416044Z",
"statusChangedAt": "2026-10-18T00:05:38.416044Z"
}
},
"server": {
"name": "io.github.beepboop2025/noisefloor",
"title": "NoiseFloor — market attention and evidence checks",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"remotes": [
{
"url": "https://api.seiche.info/noisefloor/mcp",
"type": "streamable-http"
}
],
"version": "0.4.3",
"packages": [
{
"version": "0.4.3",
"transport": {
"type": "stdio"
},
"identifier": "noisefloor",
"registryType": "pypi"
}
],
"repository": {
"url": "https://github.com/beepboop2025/noisefloor",
"source": "github"
},
"description": "Offline market diagnostics, news repetition, data coverage and statistical checks for AI agents."
}
}