Remote MCP server for Index One: query financial index data, run backtests, and deploy systematic investment strategies from any MCP client.
git clone https://github.com/index1one/indexone-mcp{
"mcpServers": {
"indexone-mcp": {
"command": "node",
"args": ["/path/to/indexone-mcp/dist/index.js"]
}
}
}MCP Servers overview
# Index One MCP Server
Remote [MCP](https://modelcontextprotocol.io) server for [Index One](https://indexone.io) — query financial index data, run backtests, and build and deploy systematic investment strategies from any MCP-capable client.
| | |
|---|---|
| **Endpoint** | `https://api.indexone.io/mcp` |
| **Transport** | Streamable HTTP (stateless, POST only) |
| **Auth** | OAuth 2.1, or a team API key in `x-api-key` |
| **Tools** | 22 |
| **Registry** | [`io.indexone/mcp`](https://registry.modelcontextprotocol.io/v0/servers?search=io.indexone) |
| **Docs** | https://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 pipeline operations and datasets available, preview a pipeline 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/`](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**](TOOLS.md).
| Group | Tools |
|---|---|
| Index data | `get_index`, `get_index_values`, `get_index_holdings`, `get_index_weightings`, `get_index_universe`, `get_index_stats` |
| Backtesting | `run_backtest`, `get_backtest` |
| Discovery | `list_operations`, `get_operations`, `list_examples`, `get_example`, `list_workflows`, `get_workflow`, `list_datasets`, `inspect_dataset` |
| Preview | `run_pipeline`, `inspect_run`, `get_column_values` |
| Persistence | `validate_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 pipeline
get_operations exact parameter schemas
inspect_dataset real columns, real values
run_pipeline preview against real data (nothing saved)
validate_workflow manifest, wiring and structure check
save_workflow persist as a draft
run_backtest historical performance
deploy_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 return a `backtest_id` (and, for deploys, the pending `index_id`) immediately; poll `get_backtest` for the result.
## Support
Questions, higher rate limits, or anything odd: support@indexone.io
What people ask about indexone-mcp
What is index1one/indexone-mcp?
+
index1one/indexone-mcp is mcp servers for the Claude AI ecosystem. Remote MCP server for Index One: query financial index data, run backtests, and deploy systematic investment strategies from any MCP client. It has 0 GitHub stars and was last updated today.
How do I install indexone-mcp?
+
You can install indexone-mcp by cloning the repository (https://github.com/index1one/indexone-mcp) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is index1one/indexone-mcp safe to use?
+
index1one/indexone-mcp has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.
Who maintains index1one/indexone-mcp?
+
index1one/indexone-mcp is maintained by index1one. The last recorded GitHub activity is from today, with 0 open issues.
Are there alternatives to indexone-mcp?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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