Embedded Docs is answering right now. Last checked 11 min ago. It exposes 3 tools. Last commit 20 Jun 2026.
Page-cited retrieval for embedded docs, datasheets, MISRA, CMSIS, and RTOS references.
Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 20 September 2026. No other catalogue keeps this.
We read the source, 6 d ago · tools taken from the live server · rules 995398eba69f
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
subprocess.run(["ffmpeg", "-y", "-v", "error", "-i", os.path.join(tmp, "f%04d.png"),
frame(i / FPS * 1000).save(os.path.join(tmp, f"f{i:04d}.png"))
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 11 min ago.
claude mcp add embedded-docs --transport http https://mcp.byteask.ai/mcp
https://mcp.byteask.ai/mcp
[mcp_servers.embedded-docs]
url = "https://mcp.byteask.ai/mcp"
{
"mcpServers": {
"embedded-docs": {
"url": "https://mcp.byteask.ai/mcp"
}
}
}
{
"servers": {
"embedded-docs": {
"type": "http",
"url": "https://mcp.byteask.ai/mcp"
}
}
}
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
get_context
search_docs
request_document
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://mcp.byteask.ai/mcp | streamable-http | answering | 1611 ms | 11 min ago |
One MCP server for web search, page extraction, and cited research.
Local retrieval for AI agents: index code, docs, PDFs, data in SQLite; 24 parsers, served via MCP.
Embedded, local-first memory and retrieval for AI agents. One SQLite file, no server, no API key.
Verified doc corpora for agents: grep-first retrieval, hashed pages, Merkle+RFC-3161 receipts
MCP server for querying and retrieving Qiskit documentation, guides, and API references
Datasheet values, tables and graphs from the manufacturer's original, cited by document and page.
Shared, versioned knowledge for AI coding agents: cited retrieval and publishing of OKF bundles.
Paid x402 API and MCP for trusted public master data, golden records, and reference data.
Answers built from our own checks of this server.