Historical Edge

io.github.joachimglassell-ship-it由 GitHub 帳號 joachimglassell-ship-it 發布v1.0.0更新於 Nov 7, 2026

Precomputed, source-traced historical equity study results for AI agents; not trading signals.

發布方自己的服務:Edge Network

已驗證Streamable HTTP可網頁執行金融資料與分析

概覽

AI 產生的概覽

遠端 MCP 伺服器,依受支持的研究與時間跨度回傳預先計算、可溯源的歷史股票研究統計資料。

可以做什麼
  • 依研究 ID 與天數跨度評估受支持股票假設的歷史證據
  • 回傳結構化 JSON,包含樣本數、平均與中位數報酬、正向結果比例等統計量
  • 對不受支持或未經驗證的研究回傳 not_supported 或 not_available,而非自行計算
適用情境
適合需要某項既定股票研究的歷史報酬統計、又不想自行蒐集價格、重建財報事件或執行回測的情境。它屬於研究決策支援,不是交易訊號。
執行需求
需要遠端 Streamable HTTP 端點;此 MCP 工具未宣告任何套件、帳號、API 金鑰或請求標頭。用戶端需支援 Streamable HTTP。
安裝前請注意
結果是預先計算的研究統計,不是交易訊號,也不代表可投資組合績效;事件層級的報酬不應解讀為組合報酬。只有受支持的研究 ID 才會回傳資料。README 另描述其他 A2A 與市場資料端點,含速率限制與內部測試權杖標頭,皆不屬於此 MCP 工具。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Historical Edge,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.joachimglassell-ship-it%2Fhistorical-edge/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": {
    "historical-edge": {
      "type": "http",
      "url": "https://machine-job-fishing-net.onrender.com/historical-edge/mcp/"
    }
  }
}

README

machine-job-fishing-net

V0 experiment for machine-callable jobs and agent demand discovery

Company Delta A2A v1 experiment

The service publishes a minimal A2A 1.0 Agent Card at /.well-known/agent-card.json and accepts JSON-RPC at /a2a/company-delta. SendMessage starts a tracked Company Delta task and GetTask polls it. Discovery and polling never run the analysis engine.

Send structured input as an A2A data part:

json
{  "jsonrpc": "2.0",  "id": "request-1",  "method": "SendMessage",  "params": {    "message": {      "messageId": "message-1",      "role": "ROLE_USER",      "parts": [        {"data": {"company": "Intel Corporation", "since": "2024-12-01"}}      ]    },    "configuration": {"returnImmediately": true}  }}

Poll the returned task ID with GetTask. Completed output is an application/json artifact. Cost safeguards default to one concurrent A2A job and three accepted jobs per client IP per hour. Configure them with A2A_MAX_CONCURRENT_JOBS and A2A_RATE_LIMIT_PER_HOUR.

For controlled production verification, set A2A_INTERNAL_TEST_TOKEN and send its value only in the X-A2A-Test-Token header. This labels the traffic as internal in structured logs without logging the token.

Local setup and tests:

text
python -m venv .venv.venv/Scripts/activatepython -m pip install -r requirements-dev.txtset OPENAI_API_KEY=your-keypython -m pytest -quvicorn main:app --reload

The tests mock the costly OpenAI-backed analysis. A real Company Delta job requires OPENAI_API_KEY; never commit that value.

TSRE MCP server

The service exposes one free MCP tool over the standard Streamable HTTP transport:

  • Endpoint: https://machine-job-fishing-net.onrender.com/mcp/
  • Tool: get_sweden_market_intelligence
  • Input: none
  • Output: the latest structured TSRE Daily Investment Desk from feeds/tsre_daily.json

The feed includes Swedish equity market regime, breadth, sector rotation, RS20 candidates, Tactical Radar, data-quality information and the original research contract. It is research decision support, not autonomous investment advice, a buy/sell signal, or an order generator.

Connect any MCP client that supports Streamable HTTP to the endpoint above, then list and call the tool. For example, with the official Python SDK:

python
import asynciofrom mcp import Client

async def main():    async with Client("https://machine-job-fishing-net.onrender.com/mcp/") as client:        tools = await client.list_tools()        result = await client.call_tool("get_sweden_market_intelligence", {})        print(result.structured_content)

asyncio.run(main())

來源:README.md,提交 e9d0f74

工具

1

get_historical_edge

Evaluate historical evidence for a supported equity hypothesis without collecting historical prices, reconstructing earnings events, running an event backtest, or calculating performance statistics yourself. Returns structured JSON with sample size, mean and median returns, positive outcome rate, methodology, source provenance, and limitations. Currently supports only pead_nordic_pre_report_drift_20d_q5 (Nordic pre-earnings price drift, top quintile Q5) at 20 or 40 trading days. Precomputed event-level research only: not an arbitrary backtest, live trading signal, or proof of investable portfolio performance.

輸入參數study_id必填horizon_days必填

版本歷史

1
  1. v1.0.0最新Nov 7, 2026

評分

已滿足適用檢查項的 90%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

    請在儲存庫或註冊中心條目中宣告授權條款。

其他 Edge 整合