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AIsa

The resource layer for AI agents: one MCP endpoint and one key for web search, SEO, social, finance, crypto, prediction markets, people and company data, and LLMs.

Authority
50 reach 5 · trust 5 · quality 25 · freshness 15
Tier
listed
llms.txt
https://aisa.one/llms.txt
llms-full.txt
https://aisa.one/llms-full.txt
Sections
7
Links
47
Size
11453 bytes
Popularity rank
#915476
Categories
Marketing · AI and machine learning
For agents
Documentation: developer or product docs worth reading, nothing to call
First seen
2026-10-19T10:41:17.019Z
Last checked
2026-10-20T19:29:26.877Z
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Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-20T19:29:09.765Z. Cached copy · Source on aisa.one

# AIsa

> The resource layer for AI agents: one MCP endpoint and one key for web search, SEO, social, finance, crypto, prediction markets, people and company data, and LLMs.

This is the setup guide for agents. Read it top to bottom; load "Optional" links only when the task needs them.

## 1. Connect

Pick the first option that applies. Run the command yourself; the user only approves the browser sign-in.

### A. Your client supports remote MCP and can open a browser (default)

Add a remote MCP server named `AIsa` with URL `https://mcp.aisa.one/mcp` (Streamable HTTP), using your client's own command or config file. Auth: browser OAuth, no key needed. In a chat app (Claude, ChatGPT), the user adds it as a custom connector in settings.

Adding the server does not always start sign-in. If no sign-in window opens, start it from the client's own MCP authentication entry (a menu, command, or connector button); if only the user can reach that entry, tell them where it is. Sign-in is the slow step, not the API. Before it starts, tell the user in one line that an AIsa sign-in window or card is about to open and to click **Allow** (one click if the browser is already signed in to AIsa). Do not call step 2 until the user says sign-in is done or the AIsa tools appear; calling it earlier only returns 401, so do not retry in a loop.

If the client must restart to load the server, tell the user and wait. If you cannot add the connector yourself (sandbox, permission denied), give the user the server name and URL above and wait. Do not fall back to another method.

### B. Your client supports remote MCP but has no browser (CI, SSH, container)

Same endpoint, with the header `Authorization: Bearer $AISA_API_KEY` set in your client's MCP config instead of browser sign-in.
If `AISA_API_KEY` is not set, ask the user to create a key at https://console.aisa.one/api-keys and set it in the environment; never ask them to paste it into chat. Never print, log, or commit the key.

### C. The client has no MCP support

Use the CLI: `npm install -g @aisa-one/cli && aisa login` (Node.js 18+). Guide: https://aisa.one/docs/get-started/cli.md

### D. Calling AIsa over HTTP from your own code

- LLMs, OpenAI-compatible: `https://api.aisa.one/v1` (Gemini GenerateContent: `https://api.aisa.one/v1beta`)
- Data APIs: `https://api.aisa.one/apis/v1`
- Auth: `Authorization: Bearer $AISA_API_KEY`
- Exact paths and schemas: https://aisa.one/docs/api-reference

## 2. Verify

Make one free authenticated call on the interface you connected:

- MCP (A, B): call `account` (no arguments). If it is not in the tool list, call `use` with `{"operation_id": "account"}` instead. Returns the key, balance, and usage.
- CLI (C): `aisa balance`. (`aisa whoami` is local only and does not count.)
- HTTP (D): `GET https://api.aisa.one/v1/credits/balance` with the Bearer header returns 200 with the balance: a free protected call, the same check `aisa balance` makes. `GET /v1/models` is only a transport check;
…

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