MCP server

The Model Context Protocol (MCP) is an open standard, so the TextToQuant MCP server works with any MCP compatible AI agent, not just one. Claude, ChatGPT, Cursor, Cline, VS Code and other MCP hosts all connect to the same server. Ask it, in plain words, to build and test a strategy and it will parse, run, and read back the results. It uses the same billing, plan limits, and account as the app. There are two ways in.

Hosted connector (OAuth)#

The hosted server URL is the same for every client:

https://www.texttoquant.com/api/mcp

You sign in with your TextToQuant account (no API key needed) and approve access on a consent screen. See and revoke every connected agent anytime from Connected apps.

The hosted connector works on every plan. It needs no API key and no separate entitlement. Tools that a plan does not include (Monte Carlo on Pro, say) return a plan_required error at call time rather than being hidden, and runs bill the same credits as the app. API keys, for the REST surface and the downloadable server below, are a separate Enterprise feature.

One click install#

Add the server to your editor in one click, then sign in and approve access:

• Add to Claude
• Add to Cursor
• Add to VS Code
• Add to LM Studio
• Add to Goose

Claude organization admins can prefill the org-wide dialog instead, which adds the connector for everyone in the workspace: Add for the whole organization.

Claude Code takes one line, with no API key and no config file to edit:

claude mcp add --transport http --scope user texttoquant https://www.texttoquant.com/api/mcp

Then run /mcp inside Claude Code to finish the browser sign in. --scope user registers the server for every project on the machine; drop it to add it to the current directory only.

Grok CLI takes the same shape (no scope flag, it already writes the user-level config):

grok mcp add --transport http texttoquant https://www.texttoquant.com/api/mcp

Gemini CLI installs the TextToQuant extension, which wraps the same server plus a briefing the agent reads:

gemini extensions install https://github.com/Youssef2784/texttoquant-gemini-extension

Then run /mcp auth texttoquant inside Gemini CLI to finish the browser sign in.

Claude Code plugin is the alternative to the one-liner above when you want the server and a TextToQuant skill (how to read a result honestly, when to stress-test, what bills credits):

claude plugin marketplace add Youssef2784/texttoquant-claude-plugins
claude plugin install texttoquant@texttoquant

ChatGPT and other clients add the same URL by hand with the per client steps below.

Claude#

Add to Claude opens the Add custom connector dialog with the name and URL already filled in. Press Add, sign in with your TextToQuant account, and approve access.

To do it by hand instead: Settings → Connectors → Add custom connector, and set the URL to https://www.texttoquant.com/api/mcp.

ChatGPT#

ChatGPT reads remote MCP servers in developer mode (Plus, Pro, Business, Enterprise and Edu, on the web app).

1. Settings → Connectors (Apps), open Advanced, and turn on Developer mode.
2. Back in Connectors, create a connector: give it a name, set the MCP Server URL to https://www.texttoquant.com/api/mcp, and choose OAuth for authentication.
3. Connect, sign in with your TextToQuant account, and approve.
4. Start a chat, enable the connector, and ask it to run or show a backtest. In ChatGPT the show_* tools additionally render as an inline, interactive report widget.

Cursor#

1. Cursor Settings → MCP → Add new MCP server (or edit ~/.cursor/mcp.json for a global server, or .cursor/mcp.json inside one project).
2. Add the remote server:

{
  "mcpServers": {
    "texttoquant": {
      "url": "https://www.texttoquant.com/api/mcp"
    }
  }
}

3. The first time you use it, Cursor opens a browser OAuth flow: sign in with your TextToQuant account and approve. Cursor stores the credentials for you.

Grok#

Custom MCP connectors are on the paid plans, across web, iOS and Android.

1. Go to grok.com/connectors and click New Connector, then Custom.
2. Enter https://www.texttoquant.com/api/mcp and complete the sign in.

Mistral Le Chat#

Available on every plan, including free.

1. Side panel → Intelligence → Connectors → + Add Connector.
2. Open the Custom MCP Connector tab, enter the URL above, and authorize.

Gemini#

Gemini CLI: install the extension (one line, above) and run /mcp auth texttoquant to sign in. It is also listed in the Gemini CLI extensions gallery. The Gemini app has no custom-connector screen today; Gemini Enterprise admins add the server URL above through their connector settings.

Perplexity and Microsoft Copilot#

These have no consumer-facing custom-connector screen today. Perplexity supports MCP on its enterprise plans, and Copilot through Copilot Studio with admin setup. In each case the server URL is the same one above; only the place you paste it differs.

Other clients (Cline, VS Code, Zed and more)#

Add https://www.texttoquant.com/api/mcp as a remote MCP server and complete the OAuth sign in. A client that does not support remote OAuth connectors can use the downloadable server below with an API key: the public repo texttoquant-mcp carries the server file, a README, and an llms-install.md an agent such as Cline can follow on its own.

Where it is listed#

• Official MCP Registry: com.texttoquant/texttoquant at registry.modelcontextprotocol.io, which feeds the GitHub MCP registry, VS Code and other catalogs.
• Gemini CLI extensions gallery: texttoquant-gemini-extension.
• Claude Code plugin marketplace: texttoquant-claude-plugins.
• Cursor plugin: texttoquant-cursor-plugin (server plus skill).
• Public server repo: texttoquant-mcp (downloadable server, llms-install.md).

The Claude and ChatGPT directory listings, and the Docker MCP Catalog, are documented here as soon as they are live.

Tools#

The server covers the whole workflow (discover, author, run, read, refine, validate, and export) plus the market screener and portfolios. You never call these by name: ask in plain language and the agent picks the right tool. Everything runs on your plan, billing, and account.

Tools tagged bills 1 spend one backtest credit; everything else is a free read. You don't need to memorize the list, the agent can call describe_capabilities to learn what the platform supports and tools/list to see every tool's schema.

Discover & author#

Run & read#

Refine by market regime#

Validate & stress-test#

Custom indicators (Pine, JavaScript, Python or CSV)#

Indicators can be authored in four ways: a Pine script compiled through TradingView, JavaScript or Python run in an isolated sandbox against real bars, or precomputed values uploaded as CSV. list_indicators and get_indicator cover all of them; delete_indicator removes any saved indicator regardless of language.

A run that uses a saved indicator is stored the way the terminal writes it: the query text carries an @"Name" tag for every indicator the run resolved, and the row records which saved sheet each name bound to. Opening that run from History turns on My Indicators, attaches those sheets, and shows the tags in the query box, so it can be edited and re-run without retyping anything. Pass the names as customIndicatorHints to parse_strategy (or savedIndicatorMapping to run_backtest) and this happens automatically.

Export#

Market screener (crypto)#

Portfolios#

Present & share#

New to the portfolio tools? parse_portfolio and run_portfolio drive a shared capital, multi asset book. See the Portfolios reference for how capital, contention and the book report work.

Resources#

Beyond tools, the server exposes your data as MCP resources, so a capable client can pull a run or indicator straight into context (an @ mention, an attach menu) without a tool call:

resources/list returns your recent runs and indicators (cursor paginated) and resources/templates/list advertises both URI shapes, so a client can construct a link to any run or indicator you own. Everything is scoped to your account.

Protocol support#

The hosted server is a full MCP resource server over the streamable HTTP transport, so capable clients get the whole protocol surface, not just tool calls:

• Cancellation: cancel an in-flight tool call; a queued backtest is stopped and its credit refunded.
• Resumable progress: a dropped run_backtest stream reconnects with Last-Event-ID and replays the events it missed, then keeps following the run on any server instance.
• Argument completion: completion/complete autocompletes backtest ids and indicator names as you type.
• Resource subscriptions & list-changed notifications, and logging (logging/setLevel → notifications/message), for clients that implement them.
• Least-privilege scopes: the server enforces coarse mcp:read / mcp:run / mcp:write scopes per tool when a token carries them, so a connection can grant an agent read-only or no-spend access. The OAuth flow itself requests only openid email.

Downloadable server#

Prefer to run the server yourself, or use a local MCP client? Download it and point your agent config at it with your API key. The download is built from the same code as the hosted server, so it carries the full tool surface above (the previous 4-tool build stays at /api/v1/mcp-server-legacy.mjs).

curl -o ttq-mcp.mjs https://www.texttoquant.com/api/v1/mcp-server.mjs
# or clone it, with a README and llms-install.md an agent can follow:
git clone https://github.com/Youssef2784/texttoquant-mcp

{
  "mcpServers": {
    "texttoquant": {
      "command": "node",
      "args": ["/path/to/ttq-mcp.mjs"],
      "env": {
        "TTQ_API_KEY": "ttq_...",
        "TTQ_API_BASE": "https://www.texttoquant.com/api"
      }
    }
  }
}

The API keys page has this config ready to copy, prefilled with your key.

Prefer calling the API directly? See the REST endpoints.