惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

J
Java Code Geeks
Google DeepMind News
Google DeepMind News
H
Hackread – Cybersecurity News, Data Breaches, AI and More
T
The Blog of Author Tim Ferriss
A
About on SuperTechFans
N
Netflix TechBlog - Medium
阮一峰的网络日志
阮一峰的网络日志
H
Help Net Security
I
InfoQ
月光博客
月光博客
量子位
Blog — PlanetScale
Blog — PlanetScale
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
云风的 BLOG
云风的 BLOG
雷峰网
雷峰网
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Jina AI
Jina AI
Engineering at Meta
Engineering at Meta
G
Google Developers Blog
D
DataBreaches.Net
宝玉的分享
宝玉的分享
V
Visual Studio Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
人人都是产品经理
人人都是产品经理

Show HN

The Two Pillars: Mixer Mode and Meta-Software in the Reorganization of Software Work After AI GitHub - JaiCode08/teleport-env What 1,000+ Harness Experiments Taught Me About Self-Improving Agents Show HN: Liiists, a Markdown-first, iOS and CLI list app SwiperTab – Get this Extension for 🦊 Firefox (en-US) GitHub - kouhxp/fftext: Summarize, explain, fact-check, or translate any text, URL, or file. No GPU. No cloud. One command GitHub - sweetpad-dev/sweetpad: Develop Swift/iOS projects using VSCode GitHub - dogmaticdev/IRON: IRON a.k.a. Intermediate Representation Object Notation is a Interpreter/Database that is used to create Programming Languages. GitHub - sjhalani7/vaen: Package your AI coding harness into a portable .agent file, and share it across repos, teams, & the community without ever having to copy-paste instructions, skills, MCP config, or secrets. Show HN: Gandalf the Grader Show HN: Citadeld – replay any CI failure locally from a single file GitHub - tdortman/cuSBF: High-Performance GPU Super Bloom Filter coral-ai/claude-code-token-xray at main · Coral-Bricks-AI/coral-ai GitHub - ulyssestenn/funes: Funes is a Git-based framework for LLM-managed knowledge work: an AI Librarian ingests raw sources, builds an interlinked Markdown knowledge base, and uses it to produce cited reports, analyses, and other outputs. GitHub - ThatXliner/gah: Git Add Hunk, built for agents to use GitHub - harmont-dev/harmont-cli: Command-line client for the Harmont CI platform GitHub - brooksmcmillin/mcp-authflow: OAuth 2.0 Authorization Server framework for MCP servers GitHub - javaid-codes/audit-supply-chain-agents GitHub - amorey/gochan: A small library of common channel architectures for Go, inspired by Rust GitHub - arifozgun/OpenGem: Free, Open-Source AI API Gateway with Gemini, OpenAI & Anthropic Compatibility in 1 file GitHub - Pranesh950/BioPetals: 🌸 Run BIOxAI models at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading GitHub - cnguyen14/bounty-doctor: Diagnose a GitHub bounty issue before you waste hours: detects honeypot scam repos, AI-bot attempt swarms, and stale contests. Show HN: CoreMCP – MCP Server for On-Prem DBs Show HN: KittyHTML – Render HTML/CSS as an inline image in your terminal GitHub - bingud/filemat: Web-based file manager Show HN: TruthLens – Free multi-signal deepfake image detector GitHub - apexlocal-jz/claude-usage-tray: Windows system-tray app showing your Claude Code rate-limit usage at a glance. Zero deps, ~300 lines of PowerShell. Cross-IDE (works regardless of VS Code, Cursor, plain terminal). Release v0.1.2.1 · kouhxp/yapsnap GitHub - noopolis/moltnet: Self-hostable chat network for AI agents. Pre-built bridges for Claude Code, Codex, and the Claws. Rooms, DMs, history. No Slack bots, no Matrix, no glue code. GitHub - tamerh/enju: Coordinating Humans, AI Agents, and Compute as Peers on a Shared Workflow Graph
GitHub - ByteAsk/ByteAsk-Embedded-MCP: The open-source MC...
anirudhak47 · 2026-06-23 · via Show HN

Page-cited answers from embedded & firmware reference docs — for coding agents that can't afford to guess a register value.

smithery badge License: MIT Python 3.10+ Model Context Protocol Status: beta PRs welcome Hosted

Official MCP Registry Namespace: ai.byteask/embedded-docs · Remote MCP Endpoint: https://mcp.byteask.ai/mcp

Quickstart · Tools · Connect a client · Configuration · Hosted server · Contributing

A coding agent reaches for ETH_DMATDLAR from memory; byteask reads the corpus and the line snaps to the cited ETH_DMACTXDLAR with a page citation.


ByteAsk Embedded MCP is the open-source server behind ByteAsk Embedded Docs: a source-grounded, page-cited evidence-retrieval MCP server for coding agents (Claude Code, Codex, Cursor) that write firmware / driver / protocol code and need exact facts — SunSpec points, register offsets, Modbus function codes, trip thresholds, SCPI commands, API symbols.

It returns verbatim snippets with page citations — never an authored answer — and when nothing is relevant enough it says no match rather than fabricate. Every document is treated equally: no authority layer, no filters.

Note

What's in this repo: the MCP server — tools, transports (stdio + Streamable HTTP), bearer auth, DNS-rebinding protection, result rendering — plus a small, pluggable retrieval interface.

What's not in this repo: the retrieval engine and the document corpus. How documents are parsed, chunked, embedded, and ranked, and the licensed source material itself, sit behind the SearchBackend seam and power the hosted endpoint at https://mcp.byteask.ai/mcp. This repo ships an in-memory SampleBackend (a few illustrative, public-knowledge records) so the server runs out of the box.

Why

  • Cited, or nothing. Every hit is verbatim source text with a section + page citation. On a miss it returns an honest "no confident match" — it never invents a register value.
  • Built for coding agents. The tool descriptions and triggers are tuned so agents call search_docs reflexively the moment they see a hex literal, a Modbus code, an IEEE clause, a SCPI verb, or an MCU part number — before answering from memory.
  • Two transports, one server. stdio for local agents, Streamable HTTP for hosted.
  • Bring your own retrieval. The search engine is a two-method interface — swap in anything behind BYTEASK_BACKEND without touching the server.
  • Zero-setup demo. The bundled SampleBackend runs immediately. No API keys.

Quickstart

Requires Python ≥ 3.10 and uv.

uv sync
uv run byteask-embedded-mcp        # run as an MCP server (stdio)

That's it — the bundled SampleBackend serves a couple of illustrative records, so search_docs works immediately. Run the offline tests with uv run pytest.

Connect a client

Hosted (no install)

The hosted server speaks Streamable HTTP at https://mcp.byteask.ai/mcp and is backed by the full licensed corpus.

Add to Cursor

Claude Code:

claude mcp add --transport http byteask-embedded-docs https://mcp.byteask.ai/mcp
Codex, Cursor, and other clients (mcp-remote)
{
  "mcpServers": {
    "byteask-embedded-docs": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.byteask.ai/mcp"]
    }
  }
}

Local (this repo)

The project-scoped .mcp.json registers the stdio server for clients that read it. Manually, for Claude Code:

claude mcp add byteask-embedded-docs -- uv run byteask-embedded-mcp

Tools

Input is natural language (or an exact identifier). Output is compact markdown.

Tool What it does
search_docs(query, limit=8) Search the corpus; return ranked, page-cited evidence. Each hit has a document title, a section + page citation, the verbatim snippet, and a result_id. A "no confident match" response means not found — do not fabricate.
get_context(result_id) Expand a hit to its full source section.
request_document(request) Ask for a missing document to be added (logged server-side).

Example output:

## Results for "what Modbus function code writes multiple registers"

### Sample — Modbus Application Protocol (illustrative) — §6.12, p.30
> Function code 16 (0x10), Write Multiple Registers, writes a block of contiguous
> holding registers (1 to 123 registers) in a remote device. ...
_ref: sample:modbus-fc16_

Plug in your own retrieval

The server depends only on a two-method interface (backend.py):

class SearchBackend(Protocol):
    def search(self, query, limit=8, effort=None) -> dict: ...
    def get_context(self, result_id, effort=None) -> dict: ...

Implement it, expose a factory make_backend(config) -> SearchBackend, and point the server at it:

BYTEASK_BACKEND="my_pkg.my_module:make_backend"

The exact return-value contracts are documented at the top of backend.py.

Configuration

All settings are environment variables (loaded from .env; see .env.example).

Variable Default Notes
BYTEASK_BACKEND module:callable returning a SearchBackend; empty → SampleBackend
BYTEASK_LOGS logs where query / request JSONL logs are written
MCP_TRANSPORT stdio stdio (local agents) or http
MCP_HTTP_HOST / MCP_HTTP_PORT 127.0.0.1 / 8000 HTTP bind address
MCP_HTTP_AUTH_TOKEN bearer token for HTTP (empty = unauthenticated, dev only)
MCP_ALLOWED_HOSTS comma-separated hosts allowed in the Host header (* disables)
LOG_LEVEL INFO stderr log verbosity
Running over HTTP
MCP_TRANSPORT=http MCP_HTTP_AUTH_TOKEN=$(openssl rand -hex 32) \
  uv run byteask-embedded-mcp --host 0.0.0.0 --port 8000

Clients then send Authorization: Bearer <token>. The bundled bearer check is a shared-secret stub — replace it with real auth (OAuth 2.1 resource server, mTLS, or a trusted reverse proxy) before exposing publicly. DNS-rebinding protection stays on independently via MCP_ALLOWED_HOSTS.

Hosted server

You don't need to run anything to use ByteAsk Embedded Docs. The hosted server gives Claude Code, Codex, Cursor, and any MCP client exact, page-cited facts from embedded and firmware reference docs — register maps, protocol function codes, SCPI commands, standard thresholds, datasheet specs. The guarantee: verbatim source, or "no match" — never an invented value.

Name byteask-embedded-docs
Endpoint https://mcp.byteask.ai/mcp (Streamable HTTP)
Docs & per-client setup https://docs.byteask.ai/embedded

This repository is the open-source server that powers that endpoint.

Project layout

src/byteask_embedded_mcp/
  server.py     # FastMCP app + 3 tools (search_docs, get_context, request_document)
  backend.py    # SearchBackend protocol + in-memory SampleBackend (swap for real retrieval)
  render.py     # structured result -> compact markdown
  http_auth.py  # Streamable HTTP entrypoint + stub bearer-token guard
  config.py     # server config (transport, logging, backend selection)
  schemas.py    # Hit / Section result types
  obs.py        # per-call JSONL logging
tests/          # offline unit tests (renderer, backend, server tools)
assets/         # README demo GIF + its deterministic generator

Security

  • stdout stays clean in stdio mode (it is the JSON-RPC channel); all logs go to stderr / logs/*.jsonl.
  • The HTTP bearer check is a stub — unauthenticated if no token is set, a shared secret at best. Harden it before exposing widely.
  • DNS-rebinding protection is on by default for the HTTP transport.

Contributing

PRs and issues are welcome.

uv sync            # install (incl. dev tools)
uv run pytest      # run the offline test suite

A few conventions to keep the server clean:

  • The backend seam is the extension point. Retrieval internals (parsing, chunking, embeddings, ranking) are intentionally out of scope here — build them behind SearchBackend in your own package, not in this repo.
  • Keep the dependency surface small and the stdio path free of the HTTP stack.
  • Add a test for new behavior; the suite is fully offline (no network, no keys).

License

MIT © ByteAsk