Historical Edge

io.github.joachimglassell-ship-it由 GitHub 账号 joachimglassell-ship-it 发布v1.0.0更新于 Nov 7, 2026

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

发布方自己的服务:Edge Network

已验证Streamable HTTP可网页运行金融数据与分析

概览

AI 生成的概览

远程 MCP 服务器,按受支持的研究与时间跨度返回预先计算、可溯源的历史股票研究统计数据。

可以做什么
  • 按研究 ID 与天数跨度评估受支持的股票假设的历史证据
  • 返回结构化 JSON,包含样本量、平均与中位数收益、正向结果比例等统计量
  • 对不受支持或未经验证的研究返回 not_supported 或 not_available,而非自行计算
适用场景
适合需要某项既定股票研究的历史收益统计、又不想自行收集价格、重建财报事件或运行回测的场景。它属于研究决策支持,不是交易信号。
运行要求
需要远程 Streamable HTTP 端点;该 MCP 工具未声明任何软件包、账号、API 密钥或请求头。客户端需支持 Streamable HTTP。
安装前请注意
结果是预先计算的研究统计,不是交易信号,也不代表可投资组合表现;事件层面的收益不应解读为组合收益。只有受支持的研究 ID 才会返回数据。README 还描述了另外的 A2A 与市场数据端点,含速率限制和内部测试令牌请求头,均不属于该 MCP 工具。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Historical Edge,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.joachimglassell-ship-it%2Fhistorical-edge/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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())

来源: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.

输入参数study_id必填horizon_days必填

版本历史

1
  1. v1.0.0最新Nov 7, 2026

评分

已满足适用检查项的 90%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分

    请在仓库或注册中心条目中声明许可证。

其他 Edge 集成