Index One
io.indexone由 indexone.io 发布官方发布者v1.4.0更新于 Nov 2, 2026
Query financial index data, run backtests, and deploy systematic investment strategies on Index One.
概览
远程 Index One 服务器,让助手读取金融指数数据、运行回测,并构建和部署系统化指数策略。
- 可以做什么
- 读取团队及公开指数的元数据、历史数值序列、持仓、权重、股票池与风险收益统计
- 在历史数据上运行回测并查询回测结果
- 发现可用的工作流操作、示例、工作流与数据集
- 用真实数据预览工作流,并查看运行输出与列值
- 校验并保存工作流草稿,随后将指数部署为持续计算的实时指数
- 适用场景
- 当你使用 Index One 的指数,并希望助手在聊天客户端内查看指数数据、用历史数据检验策略定义,或搭建并部署自定义指数工作流时适用。
- 运行要求
- 通过 streamable HTTP 连接 api.indexone.io 远程端点,无需本地安装。认证方式为使用 Index One 账号的 OAuth 2.1,或对不支持 OAuth 的客户端在 x-api-key 请求头中提供团队 API 密钥。调用限定在所属团队范围内,速率限制约为每分钟 60 次。
安装
在 SourceWeft 中
- 打开 控制台中的 Index One,将其添加到工作区。
- 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
- 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.indexone%2Fmcp/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。其他 MCP 客户端
把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。
{
"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.
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
Cursor — ~/.cursor/mcp.json
VS Code — .vscode/mcp.json
Claude Desktop — claude_desktop_config.json
Desktop reaches remote servers through the mcp-remote bridge:
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.
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:
Operation names, dataset ids, column names and filter values are always looked up, never guessed.
Notes
- Stateless streamable HTTP: every request is self-contained,
POSTonly (GET/DELETEreturn405), JSON responses returned directly — no SSE stream required. - Preview runs cache their outputs for two hours so
inspect_runandget_column_valueswork across calls. run_backtestanddeploy_indexnever hold the connection open: they validate synchronously, then return abacktest_id(and, for deploys, the pendingindex_id) immediately; pollget_backtestfor 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]
来源:README.md,提交 61c5578
工具
0版本历史
1- v1.4.0最新Sep 16, 2026
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