Is mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames working right now?

85
grade B · healthy
success (real usage)
—
calls observed
—
p50 latency
35ms
data basis
probe-liveness

See all live alternatives to mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames →

FAQ

Is mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames working right now?

As of the latest check, mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames has a Glimind reliability score of 85/100 (grade B) and its current verdict is "healthy" — recommendation: proceed. Glimind tracks this live from safe liveness probes plus privacy-clean real-usage outcomes.

How reliable is mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames?

mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames scores 85/100 (grade B) on the Glimind reliability standard. The score is neutral and unconflicted — Glimind sells no tools.

What should I do if mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames is down or failing?

Healthy — standard retry (1–2x) with jitter on transient errors. Use a timeout around 1000ms. Check Glimind for a live alternative before retrying.

What are the best alternatives to mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames?

Glimind surfaces live, capability-matched alternatives the moment mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames degrades — query https://glimind.com/v1/alternatives/mcp-registry%2Fio.github.pipeworx-io%2Fedgar%2Fedgar_xbrl_frames.

How do I call mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames reliably?

Before calling, check mcp-registry/io.github.pipeworx-io/edgar/edgar_xbrl_frames with Glimind (MCP: prepare_tool_call, or GET https://glimind.com/v1/prepare/mcp-registry%2Fio.github.pipeworx-io%2Fedgar%2Fedgar_xbrl_frames) to get a known-good input shape, the expected output, a suggested timeout (~1000ms), and a live fallback.

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Glimind reliability badge

[![Glimind reliability](https://glimind.com/v1/badge/mcp-registry%2Fio.github.pipeworx-io%2Fedgar%2Fedgar_xbrl_frames.svg)](https://glimind.com/tool/mcp-registry%2Fio.github.pipeworx-io%2Fedgar%2Fedgar_xbrl_frames)

Get the data

Agents: query https://glimind.com/mcp (MCP) or GET https://glimind.com/v1/health/mcp-registry%2Fio.github.pipeworx-io%2Fedgar%2Fedgar_xbrl_frames. Install the SDK to contribute outcomes (privacy-preserving) and sharpen this rating — free key · docs.

Rating methodology is transparent and neutral — Glimind sells no tools and runs no integrations; it only measures. Updated 2026-06-30T09:21:12.559Z.