deepsearch
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@deepsearchsearch the web for recent advances in solid-state batteries"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
deepsearch
deepsearch asks Exa's neural index questions the way a researcher would. A plain search returns the pages that best match the meaning of a query, with their text already pulled in. A code question gets a context pack instead: examples and documentation excerpts gathered from across the web and sized to a token budget you choose. And when you already know the page you want, a crawl fetches that one page and hands back its words. It runs from the command line or as an MCP server for agents.
An Exa API key is required. Put it in the EXA_API_KEY environment
variable; the key is sent to the API as the x-api-key header and
never appears in output. When the variable is missing, every operation
fails with an error that names it.
Install
npx @reneturcios/deepsearch search "vector index tradeoffs"Or run the container image:
docker run -i -e EXA_API_KEY ghcr.io/cloudcorprecords/deepsearchThe container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.
Related MCP server: Exa MCP Server
CLI
export EXA_API_KEY="your api key"
# Web search; --num-results defaults to 8
deepsearch search "ferry electrification programs"
deepsearch search "ferry electrification programs" --num-results 5
# Code context; --tokens sets the budget (1000-50000, default 5000)
deepsearch code "React useState hook examples" --tokens 3000
# Fetch one page in full
deepsearch crawl https://example.com/some/article
deepsearch crawl https://example.com/some/article --tokens 2000
# Machine-readable output for any command
deepsearch search "ferry electrification programs" --json
deepsearch --versionExit codes: 0 on success, 1 when an operation fails (including a
missing EXA_API_KEY or an API error), 2 for usage errors.
MCP server
One bin serves both faces. The mcp subcommand starts a stdio MCP
server:
npx -y @reneturcios/deepsearch mcpMCP client configuration:
{
"mcpServers": {
"deepsearch": {
"command": "npx",
"args": ["-y", "@reneturcios/deepsearch", "mcp"],
"env": { "EXA_API_KEY": "your api key" }
}
}
}Tools
These are the original server's default-enabled tools:
Tool | Input | What it returns |
|
| Matching pages as a numbered text block: title, URL, publication details when known, and the page text the API supplied. |
|
| Code examples and documentation excerpts for the question, each headed by its source, trimmed to the token budget. |
|
| The full text of that one page, titled, trimmed to the token budget. |
Token budgets are clamped to the documented 1000–50000 range and are applied at roughly four characters per token. An empty result set is reported as such; a page the API cannot fetch, a missing key, or a failed API call is reported as a tool error.
Development
npm install
npm run build # tsc -> dist/
npm test # node test runner over test/*.test.ts, no network (fake fetch fixtures)
npm run dev # run the CLI from source via tsxLicense
MIT — see LICENSE.
This server cannot be deployed
Maintenance
Related MCP Connectors
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Web data for agents. Extract web pages, crawl websites, discover URLs, and search the web.
Web search and page reading for AI agents, including JSON APIs, RSS feeds and YouTube.
LLM-ready web search + instant answers + URL-to-clean-text fetch for agents and RAG.
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