Historical Edge

io.github.joachimglassell-ship-itPublished by GitHub account joachimglassell-ship-itv1.0.0Updated Nov 7, 2026

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

The publisher's own server: Edge Network

VerifiedStreamable HTTPWeb executableFinanceData & Analytics

Overview

AI-generated overview

Remote MCP server that returns precomputed, source-traced historical equity study statistics for a supported study and horizon.

What you can do
  • Evaluate historical evidence for a supported equity hypothesis by study ID and horizon in days
  • Return structured JSON with sample size, mean and median returns, positive outcome rate and related statistics
  • Report unsupported or unverified studies as not_supported or not_available instead of computing results
When to use it
Useful when an assistant needs historical return statistics for a defined equity study without collecting prices, reconstructing earnings events or running its own backtest. It is research decision support, not a trading signal.
Requirements
A remote Streamable HTTP endpoint; no package, account, API key or header is declared for the MCP tool. The client must support Streamable HTTP.
Before you install
Results are precomputed research statistics, not trading signals or investable portfolio performance, and event-level returns should not be read as portfolio returns. Only supported study IDs return data. The README also describes separate A2A and market-feed endpoints with rate limits and an internal test token header, which are outside the MCP tool.

Installation

In SourceWeft

  1. Open Historical Edge in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.joachimglassell-ship-it%2Fhistorical-edge/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "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())

Source: README.md at commit e9d0f74

Tools

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.

Parametersstudy_idrequiredhorizon_daysrequired

Version history

1
  1. v1.0.0LatestNov 7, 2026

Score

90% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.

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