HyperXosist-Agent Remote MCP

io.github.KG-NINJA由 GitHub 帳號 KG-NINJA 發布v2.5.1更新於 Oct 24, 2026

X feedback discovery, noise-reduced query planning, signal filtering, and AI handoffs.

發布方自己的服務:Registry Mcp

已驗證Streamable HTTP可網頁執行網頁搜尋與抓取開發者工具

概覽

AI 產生的概覽

遠端 MCP 伺服器,把 X(Twitter)研究意圖轉成降噪搜尋方案、篩選已蒐集的貼文,並產生給編碼代理的交接包。

可以做什麼
規劃 X 研究:依自然語言意圖產生降噪的官方 x.com 搜尋連結與品質分數,含抱怨、功能請求、競品訊號等範本與任務。篩選已蒐集貼文:把可處理的缺陷、功能請求與使用體驗摩擦,和空泛好評、互動誘餌及垃圾內容區分開。產生交接:把保留的意見整理成結構化的 Signal-to-Fix 套件與編碼代理提示詞。三個工具都只處理使用者提供的文字,不抓取 X 或取得貼文。
適用情境
當你希望助理規劃針對 X/Twitter 的產品意見、抱怨或社群訊號搜尋,並對已蒐集的貼文做篩選、把有用內容轉成工程交接或編碼代理提示詞時使用。
執行需求
遠端 Streamable HTTP 端點;公開免費模式未宣告驗證、環境變數或標頭。三個已公布的工具有免費,不需 X API 或 OAuth。README 提到的付費正式執行並未由公開端點提供。
安裝前請注意
README 描述以 x402 付費的執行路徑(Base 上 0.01 USDC),並警告用戶端不得自動重試已確認的付款呼叫;公開端點目前只公布三個免費工具。伺服器不抓取 X,貼文需自行蒐集,並自行遵守 X 的條款。不要提供私鑰、助記詞或錢包機密。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 HyperXosist-Agent Remote MCP,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.KG-NINJA%2Fhyperxosist-agent/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "hyperxosist-agent-remote": {
      "type": "http",
      "url": "https://mcp.kgninja.dev/mcp"
    }
  }
}

README

HyperXosist Agent

[CI] [License: MIT] [Version] [Live]

Agent-first toolkit and Remote MCP server for noise-reduced X (Twitter) search planning and Feedback-to-Fix engineering handoffs. It generates structured search plans and official X search URLs for humans and AI agents. The planning and synthetic demonstration workflow does not directly scrape X. Optional Grok Build mode is default off.

日本語の要点: X 公式検索用クエリを組み立てる静的ツールです。人間UIとAgentのplanning / filtering / handoffは無料。production executionのみx402支払い対象です。検索結果の埋め込みや自動投稿はしません。

Agent-readable summary

HyperXosist-Agent helps an AI agent turn a research intent into a structured search plan, an official X search URL, supplied-feedback filtering results, and a Signal-to-Fix engineering handoff. It is a planning and handoff layer: it does not claim to scrape X directly, publish posts, or deploy code automatically.

Free capabilities include MCP discovery, planning, filtering, structured handoff, and local dry-run workflows. Automated production use of generated search URLs and external collection use the existing x402 endpoint and return HTTP 402 until valid payment proof is supplied. Payment requirements are published at payment-options.json.

Agents must follow the applicable user or operator payment policy. They must not request private keys, seed phrases, wallet secrets, or sensitive user data. If a wallet requires human approval, the agent should ask the operator to review and approve the transaction, then retry the same request with valid x402 payment proof.


Why this exists

Raw X advanced search is powerful but easy to get wrong (spam, engagement bait, overlong excludes, one-angle keyword guesses). HyperXosist gives you:

  1. Humans — a fast dark UI to compose operators, templates, noise filters, and open official search tabs.
  2. AI agents — a sticky loop: plan → score → pay → collect → refine → Keep-filter → Grok Build / Signal-to-Fix → receipt.
Discover → Plan → Score gate → Pay (x402) → Collect → Self-heal → Keep-filter → Grok Build / Handoff → Remember

Features

For everyone

  • No X API / OAuth — opens x.com/search with a built query
  • Zero build — static HTML/CSS/JS; works on GitHub Pages
  • Privacy-friendly human path — form history in localStorage only
  • Noise Reduction — Low / Medium / High with priority-capped excludes (safe query length)
  • Advanced operators — from / to / @ / OR groups / hashtags / url: / engagement floors / media & reply filters / raw fragment
  • Research templates & date presets (24h → 1y)
  • Shareable state — URL hash #s=...

For AI agents

  • Official Model Context Protocol (MCP) Server — expose query planning, signal filtering, and downstream handoff capabilities to Cursor, Claude Code, and other LLM assistants. Read docs/MCP.md.
  • dispatchToolCall / runTool — real multi-runtime tool dispatch (no hand-written mapping)
  • toOpenAITools() / toAnthropicTools() — drop-in schemas for GPT / Claude / Grok / Llama
  • CLI bin/hyperxosist.js — shell agents get --json plan / dispatch / keep / handoff
  • exportKeepOnlyJson — keep-only machine export for any coding agent
  • planFromIntent / multi-angle missions
  • scoreQuery before spending $0.01 per paid call
  • suggestRefinements when results are empty or noisy
  • buildSignalToFixPipeline → full linked loop into Signal-to-Fix (humans: free UI steps; agents: x402)
  • buildHandoffPackage → Signal-to-Fix keep-only PR handoff package
  • Discovery: signal-to-fix-pipeline.json
  • Dual JSON + Markdown outputs on core APIs (any LLM style)
  • buildAgentPrompt — model-agnostic one-small-change implementation prompt
  • Transparent noise catalog: exportNoiseCatalog / noise.extraTerms
  • Optional Grok Build mode: createGrokBuildSession / buildGrokBuildPrompt (default off)
  • agent-tools.json — OpenAI-compatible tools (portable to Claude/Grok/Llama runtimes)
  • llms.txt + AGENTS.md multi-LLM discovery docs

Quick start (human)

  1. Open the live demo.
  2. Enter keywords (and optional OR group, users, dates, engagement).
  3. Optionally enable Noise Reduction and pick a research template.
  4. Click 最新で検索 (Latest) or 話題で検索 (Top) — or Ctrl+Enter / Ctrl+Shift+Enter.
  5. Copy query, search URL, or a shareable state link.
  6. Signal-to-Fix 手動連携(無料): 投稿を Collected signals に貼る → Handoff 生成 → Signal-to-Fix 用をコピー → Signal-to-Fix で Analyze → keep のみ使う。

Local UI:

bash
git clone https://github.com/KG-NINJA/HyperXosist-Agent.git
cd HyperXosist-Agent
npm run serve
# → http://localhost:5173

Quick start (AI agent)

Discovery order

  1. llms.txt
  2. AGENTS.md
  3. agent-use.json
  4. agent-tools.json
  5. x402-payment.json

Any runtime in 3 lines

js
const HyperXosistAgent = require('hyperxosist-agent'); // or ./agent-api.js

// 1) Register tools with your model runtime
const tools = HyperXosistAgent.toOpenAITools();     // or toAnthropicTools()

// 2) When the model calls a tool — one dispatcher for all shapes
const { ok, result } = HyperXosistAgent.dispatchToolCall(name, args);

Shell / CLI (no embed)

bash
npm run cli -- plan "Find product feedback about Acme for PR specs" --json
# or: node bin/hyperxosist.js dispatch hyperxosist_plan_from_intent \
#        --args '{"intent":"Find feedback about Acme"}' --json

One call (library sticky loop)

js
// Node
const HyperXosistAgent = require('./agent-api.js');

const session = HyperXosistAgent.startAgentSession({
  intent: 'Find product feedback about Acme for PR specs'
});

const step = session.plan.primaryStep;
if (step.score.recommendPay) {
  const paid = step.paidRequest;
  // POST paid.body → paid.endpoint
  // expect HTTP 402 until x402 payment proof, then 200
  // after authorization, open step.searchUrl and collect post texts
}

const keepOnly = HyperXosistAgent.exportKeepOnlyJson(
  ['...candidate posts...'],
  { productName: 'Acme' }
);
// → keepOnly.texts / keepOnly.signalToFixInput / keepOnly.agentPrompt

const handoff = HyperXosistAgent.buildHandoffPackage({
  productName: 'Acme',
  feedback: ['...candidate posts...']
});
// → handoff.signalToFix.input into Signal-to-Fix (keep-only only)
// → handoff.grokBuild.prompt for Grok Build

// Grok Build path
const grok = HyperXosistAgent.createGrokBuildSession(
  'Grok Build code improvement for Acme',
  { product: 'Acme', targetArea: 'auth' }
);
const prompt = HyperXosistAgent.buildGrokBuildPrompt({
  productName: 'Acme',
  targetArea: 'auth',
  feedback: ['login button does nothing on Safari']
});
// → paste prompt.markdown into Grok Build

CLI dry-run (no payment, no network required for planning)

bash
npm test
npm run quickstart
# or: node examples/quickstart.mjs "Weekly monitor about MyProduct"

ChatGPT Site Tools / WebMCP

The GitHub Pages site feature-detects document.modelContext.registerTool(...) and exposes four Site Tools in compatible browser environments.

Free, local, and read-only:

  • hyperxosist_search_plan
  • hyperxosist_filter_signals
  • hyperxosist_build_handoff

Paid production boundary:

  • hyperxosist_execute — x402 v2 production execution through https://api.kgninja.dev/hyperxosist-query

The first call omits paymentSignature and returns the server's PAYMENT-REQUIRED requirements. A compatible wallet or facilitator authorizes the payment; the caller then retries with the opaque PAYMENT-SIGNATURE value and confirmPayment: true. The site does not create, request, store, log, or echo private keys, seed phrases, or wallet passwords.

The paid tool is marked consequential and non-idempotent. Clients must not auto-retry a confirmed payment call. Browsers without WebMCP support continue to use the normal human UI unchanged.

MCP: Local and Remote

The shared MCP core contains the same economic boundary as WebMCP:

  • Three free tools: planning, supplied-signal filtering, and engineering handoff.
  • One paid tool: hyperxosist_execute, which forwards an explicitly confirmed x402 request to the existing payment Worker.
bash
# Local stdio for Cursor, Claude Code, and compatible clients
npm run mcp

# Optional private Node Streamable HTTP server
HYPERXOSIST_MCP_TOKEN="replace-me" npm run mcp:remote

Public production Remote MCP:

  • Endpoint: https://mcp.kgninja.dev/mcp
  • Health: https://mcp.kgninja.dev/health
  • Transport: Streamable HTTP
  • Public free-mode authentication: none
  • Private/self-hosted authentication: optional Bearer token
  • Currently deployed tools: hyperxosist_search_plan, hyperxosist_filter_signals, hyperxosist_build_handoff
  • hyperxosist_execute: implemented and tested in the repository, but requires an explicit production Cloudflare Worker deployment before the public Remote MCP advertises it

Merging this repository does not deploy the Cloudflare Worker. Until that manual deployment occurs, the live Remote MCP remains the three-tool free service. The WebMCP paid tool is independent of that deployment and calls the already-live x402 endpoint directly.

The existing x402 route is the only verifier and settlement boundary. MCP and GitHub Pages never create or verify payment proofs. Remote MCP telemetry must not log request content or PAYMENT-SIGNATURE; settlement analytics remain authoritative in the x402 Worker.

bash
npm run openai:remote-check
npm run test:tool-selection
npm run test:paid-execution
npm run test:webmcp

See MCP setup and security, Remote MCP Worker deployment, and ChatGPT App preparation.

Agent handoff dry-run (offline — recommended first step)

Demonstrates the full local path from search intent → keep filter → Signal-to-Fix handoff → coding-agent prompt without network access:

bash
npm run agent-handoff-dryrun -- HyperXosist-Agent
# or: node examples/agent-handoff-dryrun.mjs "HyperXosist-Agent"

What it does (all offline):

  1. Builds an agent session / mission from intent
  2. Prints mission ID, subject, primary query, and search URL
  3. Uses built-in sample feedback (not live X data)
  4. Runs filterKeepSignals (keep vs discard)
  5. Builds buildHandoffPackage
  6. Prints Signal-to-Fix input JSON preview
  7. Prints the coding-agent implementation prompt (Markdown)

Important: this is a local dry-run. It does not scrape X, collect real posts, open the search URL, post anything, or perform x402 payment. Real agent production search still requires x402 after scoreQuery.

Payment policy (agents)

UseCost
Human browser UI and manual official X URL useFree
Local planning, scoring, filtering, and handoffFree
WebMCP free toolsFree
Remote MCP deployed planning/filtering/handoff toolsFree
hyperxosist_execute production executionx402 paid; current metadata states 0.01 USDC on Base

Execution flow:

  1. Call hyperxosist_execute with input and no payment signature.
  2. Receive HTTP 402 requirements, including the standard PAYMENT-REQUIRED response header.
  3. Authorize through a compatible x402 wallet or facilitator.
  4. Retry with paymentSignature and confirmPayment: true.
  5. Read the result and optional PAYMENT-RESPONSE; do not automatically repeat the confirmed call.

payment-options.json is authoritative for current price, asset, network, payee, and facilitator data. GitHub Pages and MCP do not verify or settle payment.


Missions agents re-run

IDPurpose
product_feedback_radarComplaints / feature asks / bugs
signal_to_fix_pipelineHarvest → PR handoff loop
competitive_intelMentions + switching language
weekly_monitor7-day cron-friendly window
launch_pulseLaunch / incident discourse
osint_entityfrom / mention / reply-to angles
grok_code_improvement_radarGrok Build: bugs / small asks / DX
ui_ux_feedback_harvestFrontend / UI friction for Grok
performance_complaint_detectorLatency / jank for Grok

Full catalog: missions.json


API surface (v2.6)

MethodRole
dispatchToolCall / runToolExecute any tool name (OpenAI/Anthropic/plain shapes)
toOpenAITools / toAnthropicToolsDrop-in tool schemas
exportKeepOnlyJsonKeep-only JSON + S2F input + agent prompt
startAgentSession(opts?)Universal session (optional mode:'grok')
planFromIntent(intent)NL → mission + scored paid steps + .markdown
buildMission(id, ctx)Named multi-angle campaign
scoreQuery(input)0–100 + recommendPay + .markdown
suggestRefinements(input, signals)Self-heal + .markdown
buildHandoffPackageSignal-to-Fix + agentPrompt (any LLM)
buildAgentPrompt(opts)Universal one-small-change prompt
exportNoiseCatalog / customizeNoiseRulesTransparent noise editing
filterKeepSignals / scoreTechnicalDepthKeep-only signal quality
buildGrokBuildPrompt / createGrokBuildSessionOptional Grok mode
buildQuery / buildSearchUrl / buildShareUrlQuery + shareable state
buildPaidRequest / buildBatchx402 payloads
getToolDefinitions / listMissionsCatalogs (Grok tools opt-in; format:'anthropic')

CLI surface

bash
npx hyperxosist plan "…" --json
npx hyperxosist dispatch <toolName> --args '{…}' --json
npx hyperxosist tools --format openai|anthropic|full --json
npx hyperxosist keep --product X --feedback '[…]' --export-keep-only --json
npx hyperxosist handoff --product X --feedback '[…]' --json
npx hyperxosist pipeline --product X --json

Repository layout

index.html, app.js, style.css, favicon.svg   # Human UI
agent-api.js                                # Single-source API (Node + browser)
bin/hyperxosist.js                          # Universal CLI (plan/dispatch/tools/keep…)
agent-use.json                              # Agent manifest (sticky loop)
agent-tools.json                            # OpenAI-compatible tools
missions.json                               # Mission catalog
llms.txt, AGENTS.md                         # Agent discovery / playbook
x402-payment.json                           # Payment metadata
top30_repost_blacklist.json                 # Bait phrase reference
examples/quickstart.mjs                     # CLI demo
examples/agent-handoff-dryrun.mjs           # Offline handoff dry-run (intent→keep→S2F)
examples/agent-session.example.json         # Session shape
paid-execution.js                         # Shared x402 402→signature→200 bridge
webmcp.js                                 # Browser Site Tools adapter
access-policy.json                        # Machine-readable free/paid boundary
mcp/tools.js, mcp/core.js                  # Shared MCP schemas + dispatch
mcp/server.js, mcp/remote-server.js         # Local stdio + Remote Streamable HTTP
examples/openai-remote-mcp.mjs              # Responses API Remote MCP example
test/agent-api.test.js                      # Agent API tests
test/mcp-*.test.js                          # stdio, remote, security, schema tests
.github/workflows/ci.yml                    # CI
LICENSE, CHANGELOG.md, SECURITY.md, CONTRIBUTING.md

Deploy (GitHub Pages)

  1. Push to main.
  2. Settings → Pages → Deploy from a branch → main / / (root).
  3. Site: https://<user>.github.io/HyperXosist-Agent/

No build step. CI runs tests on every push/PR to main.

Public integration checks

  • UI loads on GitHub Pages
  • agent-use.json / x402-payment.json / access-policy.json / llms.txt fetchable
  • Link to Signal-to-Fix agent-use.json works
  • Unpaid POST to hyperxosist-query endpoint returns 402

Disclaimer

  • Not affiliated with X Corp.
  • This tool only builds search queries / opens official search. It does not embed timelines, auto-post, or replace the X API.
  • You are responsible for complying with X’s terms and applicable law when searching or collecting content.

License

MIT © 2026 KG-NINJA

Related

MCP discovery and catalog

Machine-readable catalog metadata: https://kg-ninja.github.io/HyperXosist-Agent/mcp-catalog.json

For AI operators and agent builders

Use HyperXosist-Agent when you need to discover customer complaints, product feedback, or pain points on X/Twitter without starting with noisy ad-hoc queries.

Common use cases:

  • X/Twitter product-feedback discovery
  • Customer complaint and pain-point detection
  • Noise-reduced social listening query planning
  • Signal filtering for actionable feedback
  • AI-agent handoff generation for engineering teams

30-second Remote MCP quick start:

  1. Connect an MCP client to https://mcp.kgninja.dev/mcp using Streamable HTTP.
  2. Call initialize, then tools/list.
  3. Start with hyperxosist_search_plan using a natural-language intent.
  4. Use hyperxosist_filter_signals and hyperxosist_build_handoff on collected text.
  5. For production execution, use hyperxosist_execute: inspect the unsigned 402 requirements, authorize with a compatible x402 wallet/facilitator, then retry once with explicit confirmation.

Free MCP planning and handoff tools do not perform external collection. Human browser use remains free; automated production search execution is the paid boundary.

Optional signed artifact receipt

When a downstream agent or audit workflow requires a service-signed record of an artifact digest check, use the opt-in AVU buyer adapter. Handoff remains free; local-only checks make no network calls. The adapter checks availability, precheck digests, bound x402 terms and signed delivery. A buyer-owned wallet must explicitly authorize payment.

sh
npm run avu:demo    # offline synthetic example; never pays
npm run avu:status  # GET-only readiness check; never pays

This is a source adapter, not a new deployed Remote MCP tool or an npm release. Live wallet/settlement compatibility still requires an authorized end-to-end test after service recovery.

Agent-to-agent service matching (source preview)

Use agent-matchmaker.mjs or the new local stdio MCP server to match an agent's actual task, budget and deadline to five existing API services or an AVU artifact receipt. The client reuses the free public /match endpoint, checks advertised payment terms against live OpenAPI, and excludes local-only needs, unsupported capabilities and known same-operator purchases.

bash
npm run marketplace:demo                   # offline; no purchase
npm run marketplace:demo -- --live         # free discovery using synthetic demand
node mcp/matchmaker-server.mjs             # connect from an MCP-capable buyer

See the matching guide and machine-readable entry. Six capabilities belong to one operator; external buyer demand, brokerage fees, real payment and revenue are not created by matching. The new tools are local source only and do not change the production Remote MCP deployment.

來源:README.md,提交 6912b99

工具

3

hyperxosist_search_plan

Use only for specialized X (Twitter) research planning: complaints, bug reports, feature requests, product feedback, or community signals. Builds multiple noise-reduced official x.com/search URLs and quality scores. It is not general web search and does not scrape X or collect posts.

輸入參數intent必填

hyperxosist_filter_signals

Use after X posts or tweet text have already been collected. Separates actionable bugs, feature requests, and UX friction from empty praise, engagement bait, and spam. It does not fetch, scrape, or search X.

輸入參數feedback必填

hyperxosist_build_handoff

Use to turn previously collected X feedback into a structured Signal-to-Fix package and coding-agent prompt. It does not perform general summarization, search the web, scrape X, or modify source code.

輸入參數feedback必填productName必填

版本歷史

1
  1. v2.5.1最新Sep 16, 2026

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