Index One

io.indexone由 indexone.io 發布官方發布者v1.4.0更新於 Nov 2, 2026

Query financial index data, run backtests, and deploy systematic investment strategies on Index One.

已驗證Streamable HTTP可網頁執行效率與工作流金融資料與分析

概覽

AI 產生的概覽

遠端 Index One 伺服器,讓助理讀取金融指數資料、執行回測,並建置與部署系統化指數策略。

可以做什麼
  • 讀取團隊及公開指數的中繼資料、歷史數值序列、持股、權重、股票池與風險報酬統計
  • 在歷史資料上執行回測並查詢回測結果
  • 探索可用的工作流操作、範例、工作流與資料集
  • 以真實資料預覽工作流,並檢視執行輸出與欄位值
  • 驗證並儲存工作流草稿,接著將指數部署為持續計算的即時指數
適用情境
當你使用 Index One 的指數,並希望助理在聊天用戶端內檢視指數資料、以歷史資料驗證策略定義,或組建並部署自訂指數工作流時適用。
執行需求
透過 streamable HTTP 連線至 api.indexone.io 遠端端點,無需在本機安裝。驗證方式為使用 Index One 帳號的 OAuth 2.1,或對不支援 OAuth 的用戶端在 x-api-key 標頭中提供團隊 API 金鑰。呼叫僅限於所屬團隊範圍,速率限制約為每分鐘 60 次。
安裝前請注意
部署會註冊一個持續計算的即時指數,需在完整回測後以 confirm=true 確認;儲存草稿與部署都會變更團隊 Index One 帳號中的資料。API 金鑰具團隊範圍權限,應妥善保管,外洩時在主控台撤銷。指數資料與工作流定義會傳送至 Index One 的託管服務。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Index One,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 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.indexone%2Fmcp/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。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "index-one": {
      "type": "http",
      "url": "https://api.indexone.io/mcp"
    }
  }
}

README

Index One MCP Server

Remote MCP server for Index One — query financial index data, run backtests, and build and deploy systematic investment strategies from any MCP-capable client.

Endpointhttps://api.indexone.io/mcp
TransportStreamable HTTP (stateless, POST only)
AuthOAuth 2.1, or a team API key in x-api-key
Tools22
Registryio.indexone/mcp
Docshttps://indexone.io/docs/mcp

This repository is the public home for the server's manifest, tool reference and client examples. The server itself is hosted by Index One — there is nothing to install, build or run locally, and the server implementation is not open source.

What it does

Index One builds and calculates custom financial indices. The MCP server exposes that platform as tools, so an agent can:

  • Read index data — metadata, historical value series, holdings, weightings, universes, and risk/return statistics for your team's indices and public ones.
  • Backtest — simulate any index definition over history, with performance summaries and value series.
  • Build and deploy — discover the workflow operations and datasets available, preview a workflow against real data, validate it, save it as a draft, and deploy it as a live, continuously calculated index.

The server is a tool surface, not a chatbot: your client's own model does the reasoning and calls tools one at a time. Every call is scoped to your team.

Authentication

OAuth — clients that implement the MCP authorization spec (the Claude web and Desktop connectors, among others) need only the endpoint URL. You'll be sent to a sign-in page and log in with your normal Index One account; no key ends up in a config file.

API key — everything else sends a team API key as the x-api-key header. This covers Claude Code, Cursor, VS Code and custom agents, which register on a random local port that OAuth providers can't pre-approve. Create and revoke keys in the Index One console under Team → API Keys.

Both resolve to the same team scope. Rate limit is roughly 60 calls per minute per team; over that you get 429 with Retry-After.

Quick start

Claude (web or Desktop) — connector

Settings → Connectors → Add custom connector, paste https://api.indexone.io/mcp, leave the advanced OAuth fields empty, and sign in with your Index One account.

Claude Code

bash
claude mcp add --transport http indexone https://api.indexone.io/mcp \  --header "x-api-key: YOUR_API_KEY"

Cursor — ~/.cursor/mcp.json

json
{  "mcpServers": {    "indexone": {      "url": "https://api.indexone.io/mcp",      "headers": { "x-api-key": "YOUR_API_KEY" }    }  }}

VS Code — .vscode/mcp.json

json
{  "servers": {    "indexone": {      "type": "http",      "url": "https://api.indexone.io/mcp",      "headers": { "x-api-key": "YOUR_API_KEY" }    }  }}

Claude Desktop — claude_desktop_config.json

Desktop reaches remote servers through the mcp-remote bridge:

json
{  "mcpServers": {    "indexone": {      "command": "npx",      "args": [        "-y", "mcp-remote", "https://api.indexone.io/mcp",        "--header", "x-api-key:${INDEXONE_API_KEY}"      ],      "env": { "INDEXONE_API_KEY": "YOUR_API_KEY" }    }  }}

On Windows, use "command": "cmd" with "args": ["/c", "npx", ...] — Desktop resolves npx to a path containing a space, which breaks the launch. Write the header with no space after the colon; Desktop does not escape spaces inside arguments.

Anything else

See examples/ for a raw JSON-RPC call over curl and a Python client using the official MCP SDK.

Tools

Full reference with descriptions: TOOLS.md.

GroupTools
Index dataget_index, get_index_values, get_index_holdings, get_index_weightings, get_index_universe, get_index_stats
Backtestingrun_backtest, get_backtest
Discoverylist_operations, get_operations, list_examples, get_example, list_workflows, get_workflow, list_datasets, inspect_dataset
Previewrun_workflow, inspect_run, get_column_values
Persistencevalidate_workflow, save_workflow, deploy_index

Writes are deliberately narrow: an agent can save drafts and deploy an index — the latter only with confirm=true, after a full backtest, and never as an empty index — and there is no delete tool.

Building an index

An index workflow is a DAG of operations: a trigger that sets the schedule, operations that select, filter and weight securities, and a create_index_holdings step that turns the result into holdings. Agents discover that shape rather than assuming it. The server ships instructions telling the client's model to follow this path:

list_operations     what operations exist?get_example         copy wiring from a real workflowget_operations      exact parameter schemasinspect_dataset     real columns, real valuesrun_workflow        preview against real data (nothing saved)validate_workflow   optional draft check (the run tools validate on their own)save_workflow       persist as a draftrun_backtest        validates + simulates, returns a backtest_id immediatelydeploy_index        register a live index (confirm=true)

Operation names, dataset ids, column names and filter values are always looked up, never guessed.

Notes

  • Stateless streamable HTTP: every request is self-contained, POST only (GET/DELETE return 405), JSON responses returned directly — no SSE stream required.
  • Preview runs cache their outputs for two hours so inspect_run and get_column_values work across calls.
  • run_backtest and deploy_index never hold the connection open: they validate synchronously, then return a backtest_id (and, for deploys, the pending index_id) immediately; poll get_backtest for the result — it absorbs part of the wait server-side, so polling back-to-back is fine.

Support

Questions, higher rate limits, or anything odd: [email protected]

來源:README.md,提交 61c5578

工具

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版本歷史

1
  1. v1.4.0最新Sep 16, 2026

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